Abstract Books of the Global Conference on Business, Management and Marketing
The Global Conference on Business, Management and Marketing in the Modern Era (BMMCONF) presents carefully peer-reviewed research presented at the annual Business, Management and Marketing conference organized by Proud Pen. This collection captures original work across the field of Business, Management and Marketing, spanning theoretical frameworks to applied studies. Each volume serves as a reference for ongoing research and study in the discipline.
Reinventing Ultra-Fast Fashion: Strategic Growth Recommendations for SHEIN’s Sustainable Brand Development
Fast fashion retail faces unprecedented challenges in balancing rapid growth with increasing consumer demands for sustainability, quality, and ethical practices. SHEIN, despite being the largest fast fashion brand in the United States, experienced a decline in valuation due to shifting consumer priorities toward transparency and responsibility. This paper explores how SHEIN can evolve from a pure-play fast fashion retailer into a sustainable, premium-accessible brand through primary and secondary research analysis. A mixed-methods approach combining survey data from respondents and sentiment analysis of 1250 consumer reviews across seven digital platforms reveals three distinct consumer segments, identifying critical pain points including quality concerns and skepticism on sustainability. The research proposes a three-tiered strategic framework—namely the “SHEIN Evolution Pyramid”—encompassing operational excellence and sustainability (foundation), strategic premiumization and revenue diversification (differentiation), and omnichannel expansion and brand elevation (experience). Data-driven strategic recommendations provide a roadmap for maintaining cost leadership while addressing consumer trust, offering insights applicable to the broader challenge of the fast fashion industry’s transformation.
Copyright (c) 2026 Abstract Books of the Global Conference on Business, Management and Marketing
Riffs, Routes, and Revenue: Artificial Intelligence–Enabled, Authenticity-Constrained Tour Marketing—Insights from Rock, Hard Rock, and Heavy Metal
Rock, Hard Rock, and Heavy Metal tours are experiential products where value is co-created symbolically and communally, not only through functional service delivery (Holbrook & Hirschman, 1982). Tour marketing and revenue capture are platformed: discovery happens in social feeds and search, ticketing runs through e-commerce marketplaces, and value extends via merchandise and community engagement. This conceptual paper develops an artificial intelligence (AI)–enabled, authenticity-constrained tour marketing framework that integrates AI and big data analysis into strategic planning and performance measurement. The framework argues that AI-supported scanning of geographic signals—streaming, search, social engagement, and prior sell-through—can improve routing by reducing information frictions (Cho et al., 2018). However, optimization can trigger authenticity backlash when monetization appears extractive, because brand community norms shape legitimacy and repeat behavior (Muñiz & O’Guinn, 2001; Schau et al., 2009). Ticketing and resale are treated as risk-management issues because secondary markets can divert surplus and weaken perceived fairness (Courty, 2003). Pricing tiers, upgrades, and access policies are modeled as both economic and communications decisions in a market shaped by superstar effects (Krueger, 2005). Testable propositions specify when AI-enabled planning improves time-totrend advantage and sell-through velocity versus when it induces strategic convergence and weaker brand distinctiveness. A measurement blueprint links key performance indicators— sell-through velocity, conversion rate, customer acquisition cost (CAC), and return on advertising spend (ROAS)—to authenticity perceptions, community advocacy, and long-run fan value. Although developed for authenticity-sensitive rock subgenres, the sense–shape– capture logic generalizes to other live music contexts.
Marketing Sensemaking in Publishing: Environmental Scanning with Artificial Intelligence—Faster Insights or Faster Herding?
Publishing marketers compete in e-commerce ecosystems where discoverability is governed by search, recommendation feeds, and social amplification, compressing decision cycles for title acquisition, positioning, pricing, and integrated marketing communications (IMC). Addressing themes in artificial intelligence (AI), big data analysis, strategic planning, performance measurement, and e-commerce, this conceptual paper theorizes AI-enabled environmental scanning as a double-edged marketing capability in publishing. Building on environmental scanning (Aguilar, 1967) and AI-enabled decision support (Davenport et al., 2020), the paper proposes a Scan–Sense–Shift framework that links scanning design choices (signal breadth, source diversity, model and prompt diversity, and governance) to two competing pathways. The Insight pathway explains how AI accelerates market sensing by integrating weak signals across retailer rankings, search queries, review text, and social video, improving message–market fit, metadata quality, and search engine optimization (SEO) execution, and enabling reallocation of spend based on key performance indicators (KPIs) such as return on advertising spend (ROAS) and customer acquisition cost (CAC) (Wedel & Kannan, 2016). The Herding pathway explains how shared toolchains and reliance on highly visible signals can produce strategic convergence via informational cascades (Bikhchandani et al., 1992) and institutional isomorphism (DiMaggio & Powell, 1983), shifting portfolios toward exploitation at the expense of exploration (March, 1991). Testable propositions specify when AI scanning increases time-to-trend advantage versus when it erodes distinctiveness through copycat acquisitions, homogenized metadata/packaging, and crowded category advertising. The paper closes with governance design principles for publishers and author-entrepreneurs—source diversification, structured dissent, and exploration quotas—to capture AI speed without sacrificing publishing brands.
Beyond Functionality: An SBERT-Based Analysis of Technological Appropriation Modalities Using 50,000 Amazon Customer Reviews
Traditional models of technology acceptance primarily focus on functional attributes; however, contemporary human–machine interactions reveal complex relational dimensions that go beyond instrumental evaluation. This research aims to identify and quantify the multidimensional modalities of technological appropriation by analyzing discursive patterns in customer reviews through computational linguistics. An automated approach was employed to group reviews according to thematic similarity, relying on semantic similarity measures (SBERT-based clustering followed by k-means clustering). The corpus comprises 49,985 Amazon customer reviews systematically extracted from the Amazon Reviews 2023 dataset. The analysis reveals an optimal configuration of six clusters structured around three overarching dimensions: experiential, instrumental, and situational. The predominance of the experiential dimension confirms a paradigmatic shift toward the primacy of experience: the product is not evaluated solely for what it is, but also through the experience it affords and the context it evokes. This computational approach provides a robust alternative to declarative methods for analyzing processes of technological appropriation.
Copyright (c) 2025 Abstract Books of the Global Conference on Business, Management and Marketing
Ecosystem-Based Modularity in National Banking Systems for Cross-Border Digital Finance
The transformation of global financial architecture driven by central bank digital currencies (CBDCs), distributed ledger technologies, smart contracts, and API-based payment infrastructures increasingly challenges the institutional configuration of national banking systems. While advanced economies benefit from high institutional stability, their financial systems are characterised by dense regulatory frameworks and complex multi-jurisdictional coordination, raising transaction and governance costs associated with experimentation in digital monetary and settlement technologies. Existing literature largely addresses these challenges within closed national or regional frameworks, leaving limited space for analysing cross-jurisdictional infrastructural complementarity. This paper develops an institutional and ecosystem-based framework conceptualising national banking systems as modular components of global financial ecosystems. Selected infrastructural functions—such as testing environments, interoperability layers, and settlement mechanisms—can be functionally decomposed and allocated across jurisdictions with differing institutional characteristics without undermining monetary sovereignty. Such modularity allows advanced economies to preserve regulatory coherence while reducing coordination constraints associated with institutional change. The Ukrainian banking system is employed as an analytical illustration of an institutionally flexible and digitally mature environment, characterised by extensive cashless payments and advanced digital banking infrastructure. In this context, Ukraine exemplifies a potential experimental and infrastructural platform complementing highly regulated financial systems. The proposed model reframes national banking systems as reactive, interoperable platforms rather than territorially bounded entities, offering insights for the governance of digital monetary innovation in advanced economies.
The New Orchestration of Style: Digital Platforms and the Fashion Innovation Ecosystems
The fashion industry has reached a definitive tipping point in 2026, transitioning from a linear “push” model to a complex digital innovation ecosystem. This paper argues that the traditional brand-consumer duality is no longer the primary unit of market analysis. Instead, focus must shift to platforms as orchestrators, and as the central nervous system of global style. In this paper, we analyze how these orchestrators govern in “the new rules of innovation” through algorithmic curation and data-driven infrastructure. Through case studies of TikTok’s virality, and Farfetch’s curation, we demonstrate that brand resilience in 2026 is determined by Ecosystem Fluency: the ability to engage in real-time with decentralized actors, including creators, and AI driven agents. Our findings suggest that the most successful “first-place” brands have ceased acting as mere sellers, instead becoming active participants in a value web that prioritizes algorithmic relevance and co-creative agility. This study provides a strategic roadmap for a strategic roadmap for navigating market fragmentation and uncertainty, concluding that in an era of algorithmic governance, the orchestration of collective intelligence is the only sustainable path to market leadership.
Creativity and Sustainability of Intangible Cultural Heritage a Peking Opera Study
Intangible cultural heritage increasingly struggles to maintain vitality in the face of modernization and changing cultural consumption patterns, particularly in traditional performing arts. While creativity is widely viewed as essential to revitalizing intangible cultural heritage, how different creative elements work together in practice remains insufficiently understood. Using Peking Opera as a case study, this research explores the key creative elements that support the sustainable development of intangible cultural heritage and examines their interactions through a mixed-method approach. Social media data related to Peking Opera are first collected from Weibo and analyzed using topic modeling to capture dominant themes in public discourse. These results are then complemented by semi-structured interviews with Peking Opera performers and inheritors, offering in-depth insights into creative practices and transmission processes. The findings suggest that creativity in intangible cultural heritage emerges from the interplay of artistic innovation, audience engagement, institutional support, and apprenticeship systems. Rather than operating independently, these elements reinforce one another by shaping performance practices, strengthening cultural recognition, and supporting talent cultivation. The study further indicates that creative development rooted in tradition, instead of radical change, is more effective in preserving cultural authenticity while ensuring long-term sustainability. By adopting a dynamic perspective on creativity, this research contributes to heritage studies and provides practical implications for cultural policy, heritage management, and creative tourism.
Integration of Digital Technologies in Entrepreneurship Education: Enhancing Students’ Entrepreneurial Intention
The incorporation of artificial intelligence (AI) into digital technologies has significantly transformed pedagogical approaches, learner engagement, and the development of entrepreneurial skills within entrepreneurship education. This study investigates how AI-embedded technologies can enhance the effectiveness of entrepreneurship education by integrating intelligent tutoring systems and simulation-based activities that provide supervision and feedback. It highlights the growing use of AI and digital tools to foster student autonomy, stimulate innovative thinking, and bridge the gap between theoretical learning and real-world application. Particular attention is given to the digital tools students use when developing business strategies. The study examines the emergence and role of AI in various entrepreneurship education tools that facilitate business idea development. A mixed-methods approach was employed, including a literature review, comparative analysis of digital tool applications, and statistical analysis of survey data on students’ perceptions of AI’s usefulness in enhancing entrepreneurial intention. The results indicate that AI can substantially improve digital learning resources by offering students time-efficient, data-enriched, and guided learning experiences that better prepare them for the complexities of modern business ecosystems.
Signaling Firm Performance through Narrative Tone: Evidence from Kuwaiti Companies
Purpose: This study aims to provide evidence on whether the Chairman statements in listed Kuwaiti companies are used more for impression management or informational purposes through signaling. The study also attempts to better understand how shareholders react to the tone used in Chairman statements by analyzing Total Shareholder returns. Design/methodology/approach: The study uses a quantitative content analysis approach to collect and measure tone from chairman statements in listed Kuwaiti companies. The tone scores are then analyzed using panel regression models to examine their association with firm financial performance and market-based outcomes. Findings: The results for the main tone model show that Tone is highly significantly associated with Net income growth. This could suggest that managers utilize positive tone when company income is rising in the Kuwaiti listed company context and gives support to the signaling theory. However, the alternate tone formula showed that there was a negative and significant relationship with return on assets- leading to support for the impression management theory with regards to this variable. It also demonstrated a significant positive correlation with ROE and net income growth. The evidence suggests that impression management techniques are more closely associated with internal efficiency metrics such as ROA, whereas signaling behavior is used more for external efficiency metrics such as ROE and Net income growth. The Total return model found no relationship of significance between total shareholder returns and tone, this could lead to the conclusion that Chairman statements in this context are used more for ceremonial purposes.
From Ideation to Implementation: A Framework for Integrating Generative AI into University Entrepreneurship Curricula
Entrepreneurship education plays a critical role in developing future business leaders’ capabilities in opportunity recognition, business planning, and strategic decision-making. However, students particularly those without prior business training, often struggle with complex entrepreneurial tasks such as ideation, market analysis, and business-model formulation. These challenges can hinder the development of coherent business plans and reduce students’ confidence in entrepreneurial decision-making. Recent advances in generative artificial intelligence (AI) present new opportunities to enhance business-planning processes through scalable, adaptive, and personalized support. This paper proposes and evaluates a framework for integrating generative AI into university entrepreneurship curricula through an AI-empowered scaffolding system designed to support business-plan development from ideation to implementation. Grounded in the AI scaffolding design framework proposed by Zhu and Luo (2025), the system guides learners through structured questioning, iterative feedback, and reflective prompts across key business-planning stages, including opportunity identification, market analysis, value proposition development, and business-model design. The framework was piloted with undergraduate students enrolled in an entrepreneurship course. Data were collected from AI system interaction logs, student-developed business plans, and reflective feedback. The findings indicate that generative AI scaffolding enhanced students’ cognitive structuring of business-planning tasks, improved the internal coherence and strategic alignment of business models, and strengthened entrepreneurial self-efficacy. These outcomes are consistent with recent empirical evidence demonstrating the positive effects of generative AI on entrepreneurial intention, learning engagement, and capability development in entrepreneurship education (Park, 2023; Xie & Wang, 2025). This study contributes to the business and management literature by offering a practical framework for embedding generative AI into entrepreneurship and business-planning curricula. It further highlights the role of AI as a strategic pedagogical tool that augments human instruction and experiential learning, supporting the development of future entrepreneurs and managers capable of navigating increasingly complex and technology-driven business environments.
Cultural Districts Shape Dining Experience: Evidence from 600,000 NYC Restaurant Reviews
Urban restaurant reviews often reflect not only the quality of the food but also the broader atmosphere and neighbourhood context of the dining experience. This study examines how the cultural character of city districts shapes what customers emphasise in their reviews, using New York City as a representative case of a culturally diverse urban market. Cultural districts are identified through spatial analysis of arts, culture, and entertainment venues (including museums, theatres, galleries, and music venues), normalised by local population and area to capture neighbourhood cultural specialisations. Restaurants located within these districts are then linked to their local context. A corpus of over 600,000 Google Maps reviews of these restaurants across NYC neighbourhoods is analysed using a machine-learning topic model (BERTopic) to uncover recurring themes in diners’ comments and to quantify how strongly each theme is represented across different cultural contexts. Findings are summarised as district-level experience profiles that reveal systematic shifts in what patrons foreground, showing how cultural infrastructure acts as a place-based cue that reframes expectations, attention, and perceived value in dining encounters. These profiles advance place-based perspectives on consumer behaviour by operationalising neighbourhood cultural context at scale using digital traces, and by providing a replicable template for combining spatial analytics with text mining. Practically, the results support neighbourhood-aligned positioning and geo-segmentation: managers can tailor concept fit, service elements, and marketing messages to local cultural themes, coordinate offers around event-driven demand, and identify partnership opportunities with nearby cultural venues. By transforming unstructured reviews into actionable insights about context-specific experience salience, the study enables hospitality firms to differentiate themselves in competitive urban markets and make more informed decisions about location strategy, communications, and service design.
Strategic Perspectives on Student Recruitment in a Post-1992 UK University Context
CU Scarborough (CUS), part of the Coventry University Group (CUG), is a post-1992 UK institution established in 2015 with a mission centred on widening participation in higher education. Despite its contribution, CUS faces persistent challenges in student recruitment within an increasingly competitive and volatile higher education landscape. This study applies the SWOT–TOWS framework to evaluate internal and external factors shaping recruitment performance, alongside the Resource-Based View (RBV) to examine the institution’s strategic capabilities. A VRIO analysis is also employed to assess CUS’s capacity to achieve and sustain competitive advantage. The analysis identifies key internal strengths, including strong student support mechanisms and the advantages associated with membership of a well-established university group. However, it also reveals internal weaknesses, notably limited research activity, absence of postgraduate portfolio and ongoing resource constraints. Externally, the study highlights opportunities arising from the expansion of digital learning and continued demand from international student markets, while also recognising significant threats. These include intense competition across the sector, tightening international visa regulations, rising operational costs, and increasingly demanding student expectations. Such external pressures are examined using Porter’s Five Forces framework. Drawing on the SWOT–TOWS analysis, the study proposes strategic responses focused on enhancing inclusivity, expanding both physical and digital provision, and strengthening academic–industry partnerships. By aligning institutional strengths with emerging opportunities and addressing critical weaknesses, CUS can improve its strategic positioning in student recruitment. The findings and recommendations are also relevant to other post-1992 UK universities facing similar structural and competitive challenges.
Advancing Staff Learning at a Post-1992 UK University: A Multi-Framework Strategy
The University of the West of England, Bristol (UWE Bristol), a post-1992 UK institution, is recognised for applied learning and strong industry partnerships. However, it faces challenges in developing an effective staff learning (SL) strategy within an increasingly competitive higher education environment. This study applies the SWOT-TOWS analysis to assess internal and external influences on the School of Engineering’s SL provision. The Resource-Based View (RBV) and VRIO framework are used to evaluate UWE’s unique capabilities and potential for sustained advantage. Internal strengths include industry collaboration and innovative pedagogy, while weaknesses involve limited resources and uneven staff skills. Externally, digital learning technologies and government funding present opportunities, offset by threats such as rapid technological shifts, regulatory pressures, and competition from nearby institutions like the University of Bristol and University of Bath. PESTEL and Porter’s Five Forces frameworks highlight workforce diversity and compliance demands. Strategic recommendations include expanding e-learning, deepening industry alignment, and leveraging UWE’s sustainability ethos to stand out. By integrating sector insights with theoretical models, this study offers practical guidance for UWE and other post-1992 institutions to enhance SL strategies, aligning strengths with opportunities while mitigating internal and external risks in a fast-evolving educational landscape.
Artificial Intelligence and Marketing in E-Business: Balancing Innovation and Data Protection Compliance
The rapid development of artificial intelligence (AI) and digital technologies has significantly transformed marketing strategies. E-marketing now leverages big data through machine learning, recommendation systems, and predictive analytics, enabling companies to deliver highly personalized experiences: tailored offers, optimized customer journeys, real-time targeted advertising, and enhanced loyalty by anticipating customer needs. This evolution raises critical challenges, as AI relies on processing sensitive personal data. Companies must innovate while complying with data protection regulations. In Morocco, the CNDP enforces strict rules on consent, transparency, and data security, while internationally, the GDPR sets widely recognized standards influencing global practices. Compliance is not only a legal obligation but also a source of trust and competitive advantage. This article highlights practical applications of AI in e-marketing, such as automated campaigns, intelligent chatbots, behavioral segmentation, and consumer trend forecasting. It also addresses risks like privacy breaches, algorithmic bias, and threats to individual rights. Emphasizing responsible data governance, it advocates for integrated compliance measures that ensure both regulatory adherence and sustainable competitiveness. The study concludes that ethical, transparent, and regulated AI-driven marketing is essential for long-term business success.
Client-Driven Sustainability Priorities in Construction: Insights for Strategic Business Model Transformation
The transition toward sustainable business models in the construction sector requires not only internal organizational changes but also a deep understanding of client expectations regarding environmental, social, and governance (ESG) performance. Anchored in stakeholder theory, this study examines how client-driven sustainability priorities shape strategic business model transformation in construction. Semi-structured interviews were conducted with six key clients—three public sector and three private international organizations—selected through purposive sampling in collaboration with a leading construction company. The interviews explored perceptions of sustainability relevance, expectations for science-based CO₂ reduction targets, and the relative importance of 14 ESG aspects. Findings reveal a unanimous recognition of sustainability as an essential criterion in selecting construction partners. Although science-based CO₂ targets are not yet widely implemented, half of the respondents anticipate such requirements within the next one to two years, indicating a rapidly evolving regulatory and market environment. A clear hierarchy of client priorities emerged: ethical governance, transparency, anti-corruption measures, and employee well-being form the highest-priority group, underscoring a holistic interpretation of sustainability that extends beyond traditional environmental concerns. Mid-priority topics include waste management and biodiversity protection, while technology-driven or material-specific aspects such as BIM/LCA, use of recycled materials, and renewable diesel appear less critical for clients at present. The results offer actionable insights for construction firms seeking alignment with client expectations and strategic differentiation in a sustainability-driven market. The study highlights the need for further research involving broader client groups and longitudinal tracking of evolving sustainability requirements.
The Joy Factor: Fueling Resilience, Productivity, and Profit
Organizations continue to invest in strategy, technology, and operational systems, yet many face rising burnout, disengagement, and productivity challenges. This paper examines whether emotional climate—specifically sustained positive affect conceptualized as “joy”—functions as a measurable and strategically relevant driver of organizational performance. Drawing on interdisciplinary research from positive psychology, organizational behavior, and neuroscience, this conceptual literature review synthesizes evidence linking positive emotional states to key business outcomes. Foundational theory suggests that positive emotions broaden cognitive flexibility and adaptive capacity, while organizational research consistently associates engagement with higher productivity, increased discretionary effort, reduced turnover intention, and improved profitability indicators. Neuroscientific findings further support the role of positive affect in executive functioning and decision-making. Although joy is not isolated as a single causal variable, convergent findings indicate that sustained positive emotional climate operates as a performance multiplier within organizational systems. By reframing joy as a measurable psychological construct rather than a peripheral cultural attribute, this paper highlights its practical leadership implications in strengthening resilience, innovation, and sustainable profitability in complex work environments.
Beyond Talk: How Communication Drives Engagement and Unlocks Innovation
Achieving organizational goals depends on effective internal communication, especially as organizations operate in continually changing conditions where new challenges arise and existing ones deepen. Contemporary workforces demand transparency and more horizontal relationships, and organizations increasingly acknowledge the strategic importance of internal stakeholders. Empirical research links ineffective communication to information shortages and misunderstandings (Chmielecki, 2015; Gomes et al., 2023) and shows that effective communication improves performance (Leal D’Avila & De Montreuil Carmona, 2025), strengthens engagement (Men et al., 2021; Verčič & Men, 2023), and drives innovation (Suh et al., 2018; Islami & Mulolli, 2024). Notwithstanding, most findings derive from North America and Europe; Latin American evidence is limited (Labarca & Sadi, 2022; Yue & Thelen, 2023). Addressing this gap, we surveyed employees in Colombia (n = 200) and Mexico (n = 270) and analyzed the data using PLS-SEM. Internal communication exhibited positive direct effects on job satisfaction, work engagement, and innovation. Job satisfaction also showed positive associations with engagement and innovation. We detected no significant differences between the two countries. The article concludes with implications for theory and managerial practice in Latin American contexts.
Walking in The Light of Ecocentrism or The Darkness of Anthropocentrism: How Adopting Sustainable Practices Is Motivated by Personal Benefits
Sustainable consumption is a growing trend worldwide. Studies have examined factors behind this behaviour, often considering concerns about the environment as antecedent. However, few studies explore the adoption of this behaviour from a personal perspective, despite evidence that such a relationship exists. Based on the Theory of Protection Motivation, we propose that perceptions that environmental problems can affect personal health and well-being influence the adoption of sustainable practices at home. A sample of 1,049 adults who believe climate change and environmental problems exist is used to validate the model, employing CB-SEM for data analysis. Findings suggest that individuals do not perceive environmental degradation as harmful to their health and well-being, and that they are more likely to adopt sustainable household practices when they feel able to do so and when they don’t involve additional costs. The availability of economic resources modifies some relationships, while value orientations have a limited impact.
Brand Perception differences between Generations Y and Z in South Africa
This quantitative study tests the hypothesis that South African Generations Y and Z differ significantly in their perception of brand value. While brand perception is well-researched, direct generational comparisons are limited. An online questionnaire, based on Kotler’s Brand Perception model which measures respondent perception of Brand Purpose, Positioning, Differentiation, Identity, Trust and Beneficence, was used to collect data from a non-probability sample of Generations Y and Z, recruited via snowball sampling. Consumer Culture Theory and Planned Behaviour Theory underpins the discussion in the findings. A sample size of 100 respondents shows a weak positive correlation to the hypothesis of a significant perception difference of brand value between Generations Y and Z in South Africa. Data shows the two generations have marginal differences in their perceptions. Generation Z response data specifically shows a fairly but not significantly higher propensity in purchase intent to support brands that are socially responsible, transparent and beneficent.
Digital Tools in Entrepreneurship Education: Effects on Entrepreneurial Knowledge and Intentions
This research explores the development of entrepreneurial knowledge and intentions among students in Central and Eastern European as well as Southern European countries in the context of using digital tools within entrepreneurship education. As digitalization increasingly reshapes educational practices, entrepreneurship programs have progressively incorporated digital platforms, simulations, and online learning environments. Employing a mixed-methods approach, the study analyzes the association between students’ perceived learning outcomes, their intentions to start a business, and the application of specific digital tools, drawing on quantitative survey data alongside a systematic review and analysis of existing scholarly literature. The primary objective of the study is to evaluate the extent to which the integration of digital tools in entrepreneurship education affects both the acquisition of entrepreneurial knowledge and the development of entrepreneurial intentions among students in Central and Eastern and Southern European countries. Based on data collected from higher education institutions across several countries in the examined regions, the study offers comparative cross-national insights into the effectiveness of digital tools in supporting entrepreneurial skill development. The results indicate notable regional differences in the effectiveness of these tools and demonstrate that, although digital tools contribute positively to student engagement and knowledge enhancement, their influence on entrepreneurial intentions is shaped by cultural, institutional, and pedagogical contexts. Overall, the study enriches the existing literature on digital entrepreneurship education and provides practical implications for educators and policymakers seeking to reinforce entrepreneurship ecosystems through digitally supported learning approaches.
Volunteer Commitment in Marathon Sport Tourism: Linking Psychological Resources to Service Consistency and Visitor Experience
In the contemporary landscape of sport tourism and destination branding, large-scale road races have become signature event products that integrate event operations, visitor experience design, and hospitality service delivery. As Macao and the surrounding Greater Bay Area continue to position marathon events as year-round tourism catalysts in 2026, volunteer workforces remain a decisive yet underexplored determinant of service consistency across critical touchpoints—race-day registration and wayfinding, course support, athlete– spectator interactions, and the extended service chain that includes event partners such as official hotels and lodging providers. Events depend on volunteers. However, the psychological mechanisms linking volunteers’ internal resources to retention-oriented commitment and service reliability remain underexplored in event, tourism, and hospitality settings. This study develops and tests an integrated relationship model that links volunteers’ self-efficacy, volunteer engagement, subjective well-being, pride, and organizational commitment. By focusing on psychological dynamics, the model contributes to event management and sport tourism literature by explaining how competence beliefs and affective outcomes jointly shape volunteers’ willingness to sustain participation and uphold service standards, which are essential for protecting event reputation and enhancing destination image. A two-stage design was adopted. Prior to formal data collection, a preliminary online survey was administered among marathon volunteers via WeChat groups. After removing incomplete responses, the pilot data were used to refine a bilingual (Chinese–English) questionnaire through translation, cross-checking, and expert review, and to verify measurement reliability and validity using SPSS 26. In the main study, large-scale data collection was conducted through on-site and online distribution during the 2025 Galaxy Entertainment Macao International Marathon and the Hengqin Marathon in the Macao– Hengqin area (23 March 2025). Descriptive results indicate that sport-event volunteers are generally well educated, with the largest age group concentrated between 25 and 44 years old, and a substantial share reporting a middle-income range. Using SmartPLS to estimate the structural equation model, we find that self-efficacy positively predicts volunteer engagement, subjective well-being, and pride. Furthermore, both subjective well-being and pride significantly strengthen organizational commitment, suggesting that volunteers’ affective experiences are not peripheral but function as central mechanisms translating perceived competence into sustained attachment to event organizers. Theoretically, this research advances a more comprehensive understanding of volunteer commitment by integrating key psychological antecedents and clarifying their mechanisms in sport-event settings embedded within tourism and hospitality systems. Practically, the findings suggest that event organizers and destination stakeholders—including official hotels and lodging partners—can reduce volunteer turnover risk and safeguard service quality by strengthening volunteers’ self-efficacy through targeted training and role alignment, fostering pride via recognition and experience design, and supporting subjective well-being through volunteer-centered scheduling, timely feedback, and basic emotional support. These measures are expected to improve operational reliability, visitor satisfaction, and the consistency of service encounters across event venues and accommodation-related touchpoints, thereby enhancing the competitiveness of marathon-led sport tourism destinations.
Performance Management Improvement using AI Tools A study from Start Ups perspective
The integration of Artificial Intelligence (AI) into performance appraisal systems has revolutionized traditional evaluation methods, offering a more accurate, efficient, and unbiased approach. AI-driven tools leverage machine learning algorithms, natural language processing, and data analytics to assess employee performance comprehensively. By analyzing large volumes of structured and unstructured data, such as project outcomes, communication patterns, and peer feedback, AI ensures a more holistic evaluation. Automation reduces the administrative burden on managers, enabling them to focus on strategic aspects of talent development. AI enhances objectivity by mitigating biases often associated with human judgment, promoting fairness and equity in appraisal processes. Personalized feedback generated through AI tools offers actionable insights, fostering employee growth and engagement. Moreover, predictive analytics identify high-potential talent and flag areas needing improvement, aiding in proactive workforce management. Despite its advantages, the use of AI in performance appraisals raises ethical concerns, such as data privacy and transparency. Ensuring employees understand how AI tools work and safeguarding sensitive information are critical for successful implementation. Additionally, AI should complement, not replace, human judgment to maintain a balance between automation and the nuanced understanding of human performance. The adoption of AI in performance appraisals marks a paradigm shift, enhancing organizational productivity and employee satisfaction. By addressing its limitations and fostering a human-centered approach, organizations can leverage AI to create a more effective and inclusive performance management system.
Copyright (c) 2025 Proceeding of the Global Conference on Business, Management and Marketing
Strategic Awareness in “Società Benefit”A Pilot Study from Italy
This study presents the preliminary findings of ongoing research on a specific type of hybrid organisation: the Italian Società Benefit, introduced by Law No. 208/2015. The research draws on data from the non-financial disclosures of these enterprises. This legal business model is designed to integrate profit-making objectives with the pursuit of a common benefit. this refers to creating a positive impact, or mitigating a negative one, on individuals, communities, local areas, the environment, cultural and social heritage, public and private entities, and other stakeholders. By law, profit and common benefit purposes are required to be balanced, with neither prevailing over the other. These dual aims are embedded in the company’s bylaws, making the hybrid nature of the organisation a permanent and irreversible feature. The complexity inherent in this hybrid model requires a specific level of strategic awareness to align profit goals with those of the common benefit effectively. Formalised planning helps to mitigate potential conflicts between these objectives. Società Benefit are also subject to specific legal obligations, including the annual publication of an impact report. This document must outline the common benefit objectives pursued and assess the results achieved. given this reporting requirement, a pilot study was conducted on a limited sample of Società Benefit to identify indicators capable of capturing key features of these entities, particularly their level of strategic awareness and their inclination towards planning and programming in quantitative terms. the authors intend to present the preliminary findings of this investigation.
The Fintech-Sustainability Nexus: Analyzing Robo-Advisors’ Roles in Enhancing Financial Inclusion, Natural Resource, and Sustainable Trade for ASEAN's Economic Growth
In light of the increasing global commitments to sustainable development and regional economic integration, this study examines the influence of financial inclusion, natural resource endowments, and sustainable trade on economic growth within ASEAN nations, with robo-advisors serving as a mediating factor. Utilizing the Quantile Regression (QR) approach, the analysis uncovered three key findings. Firstly, sustainable trade significantly enhances economic growth by diminishing environmental remediation costs and improving trade efficiency, thereby confirming its direct positive impact on GDP growth through statistical analysis. Conversely, other trade measures exhibit insignificant effects, underscoring the necessity for targeted policies. Secondly, the collaboration of financial inclusion with robo-advisors unlocks GDP growth potential, as evidenced by the significant role that technology-mediated resource management plays, reflected in the consistent increase in usage. However, natural resource endowments appear to be insignificantly affected. Thirdly, with the implementation of robo-advisory technologies, the significance of sustainable trade’s contribution to GDP growth is notably enhanced. The overall results indicate that countries implementing robo-advisory systems consistently achieve improvements in the efficiency of converting natural resources into economic value. These findings provide policymakers with actionable evidence that the integration of digital financial infrastructure with sustainable trade practices can accelerate green growth while minimizing environmental costs across ASEAN economies.
Understanding Green Product Perception: The role of Price Sensitivity and Brand Awareness
This study provides insights into the role of price sensitivity and brand awareness in Generation Z’s green product perception. A quantitative method was used with the sample of 496 Generation Z respondents in Vietnam in the form of online survey questionnaires. Pearson correlations were employed to provide deeper analysis on the relationship amongst green product awareness factors including price sensitivity, brand awareness, product certification, product familiarity and customers’ trustworthiness. The study suggests that two main factors, namely brand awareness and price sensitivity were perceived as main influential factors to green product awareness. On the other hand, product certification, product familiarity and customers’ trustworthiness have less significance compared to the above factors. It is surprising that green certification is not the key determinant affecting the perception of green products while other factors such as product price and brand had significant impact. Green certifications on consuming products build trust and have considerable effect on green perception, they may also act as barriers due to cost concerns or the authenticity of the product itselves. The research findings highlighted the need for deeper understanding of the role of price sensitivity and brand awareness to increase buyers’ perception. Price modification and awareness programs should be used to bridge the gap between awareness and action. These findings provide valuable insights for businesses and marketers in promoting “eco-conscious” through pricing and branding on consuming products.
The Impact of Weak Ties' Perceived Value on Wellbeing and Dining Intention
The term "Dazi social" has recently become a hot topic on social media rapidly has become a new trend in contemporary youth socializing. This study examines the influence of perceived value of weak ties on wellbeing and dining intention within the context of "meal Dazi," while introducing social media self-efficacy as a moderating variable. Eighteen semi-structured interviews were conducted with individuals who had participated in meal Dazi activities to enrich the perceived value measurement scale. Subsequently, a questionnaire survey was administered to 505 participants who had engaged in meal Dazi activities using a structural equation model. The results showed that perceived value positively affected wellbeing and dining intention. In addition, social media self-efficacy plays a moderating role in perceived value, wellbeing, and dining intention. Accordingly, it provides theoretical contributions and practical significance.
From Compliance to Competitive Advantage: Embedding Health and Safety into Corporate Governance Strategy
In an era defined by increasing stakeholder scrutiny and dynamic global risks, this research repositions health and safety (H&S) as a strategic governance priority rather than a mere compliance function. The study explores how forward-thinking organizations are embedding H&S into board-level strategy to drive resilience, strengthen stakeholder confidence, and unlock competitive advantage. A mixed-methods approach was adopted, combining an extensive review of academic and industry literature, policy analysis, and qualitative case studies of FTSE-listed and multinational organizations with mature H&S integration practices. Semi-structured interviews with board members, HSE leaders, and governance experts provided insight into the evolving expectations of corporate leadership. Findings indicate a positive correlation between proactive H&S governance and improved organizational outcomes, including employee engagement, brand reputation, ESG performance, and operational continuity. The research identifies critical success factors such as board accountability, executive ownership of safety metrics, and alignment of H&S indicators with ESG reporting frameworks. The study recommends a governance-driven model that elevates H&S oversight to the strategic agenda, incorporating transparent reporting structures, board-level H&S committees, and performance-linked incentives. It emphasizes the need for boards to cultivate a culture of safety leadership, embed H&S into decision-making processes, and treat worker wellbeing as a material governance risk and opportunity. This research offers practical guidance to senior executives, board members, and HSE practitioners on transforming H&S from a regulatory afterthought to a cornerstone of sustainable business strategy.
Integrating IoT, AI, and Data Analytics in Food Machinery Production: A Digital Innovation Model for SMEs
The Tecnomulipast case study of a Southern Italian, small firm in the food processing machinery manufacturing industry exemplifies the company's planned digital renewal, made possible by managerial practices founded in innovation and backed by regional co-financing programs, such as those of Regione Puglia. At the heart of the change is the integration of a new Industry 4.0-compatible laser welding system into the company's infrastructure of ERP. Based on Internet of Things (IoT) technology, the system receives, transmits, and makes available both batch-level and real-time visual observations, creating a cyber-physical space for high-end manufacturing. Underpinning the change is a data analytics capability that can process both sensor measurements, KPI, as unstructured data, i.e., images, to facilitate monitoring in real-time, early anomaly, and workflow optimization. Scalable in engineering, the architecture makes possible the integration of artificial intelligence (AI) in the future to augment decision-making by predictive as well as prescriptive analytics. Beyond the overhaul of the technology, the change from the old to the new industry paradigm, Industry 4.0, was supported by a strategic model of managerialism that emphasizes organizational agility, data-driven governance, and continuous learning. Tecnomulipast's case provides the template for replicable emulation by SMEs, in general, and by companies in the digitally under-served regions, in the first instance, to demonstrate how targeted investment, leadership by innovation, and system-level integration can narrow the gap in the distance from technological capacity to operational performance in the move to Industry 4.0.
Harnessing The Power of Ai and HR Technology to Drive Global Talent Efficiency and Employee Engagement
As the global business landscape evolves at an unprecedented pace, HR technology—particularly Artificial Intelligence (AI)—is reshaping how organizations manage talent, optimize operations, and drive employee engagement. This paper delves into the transformative potential of AI and integrated HR technologies in enhancing global talent efficiency and enriching employee experiences. Focusing on the implementation of personalized learning platforms such as LinkedIn Learning, the paper illustrates how these technologies create tailored, dynamic HR services that adapt to individual employee needs. Moreover, advanced HR technologies leverage data analytics, empowering organizations to make more precise, data-driven decisions regarding talent acquisition, performance management, and retention. While the promise of AI-driven HR is significant, a critical question remains: Can AI and automation ever truly replace the human element in HR, or are we creating a "Frankenstein" system that risks losing the empathy and intuition central to effective people management? As we continue to develop and rely on AI, there is a growing concern that this "Frankenstein monster" could inadvertently begin to erode the very jobs it was designed to improve. This paper explores these emerging trends, offering insights into how organizations can harness HR technology for sustainable growth, while also addressing the ethical considerations of balancing automation with the human touch.