Abstract Books of the International Conference on Business, Management and Leadership
The Abstract Book of The International Conference on Business, Management and Leadership (ICBML) presents carefully peer-reviewed research presented at the annual Business, Management and Leadership conference organized by Proud Pen. This collection captures original work across the field of Business, Management and Leadership, spanning theoretical frameworks to applied studies. Each volume serves as a reference for ongoing research and study in the discipline.
Sustainable Marketing and Purchase Intention among Generation Z Consumers: The Mediating Roles of Brand Image and Perceived Value and the Moderating Role of Social Influence
This study examines the influence of sustainable marketing on purchase intention among Generation Z consumers, incorporating the mediating roles of brand image and perceived value, as well as the moderating role of social influence. Data were collected from 290 respondents who had prior experience purchasing sustainable products. The proposed research model was analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that sustainable marketing has a positive and significant effect on both brand image and perceived value. In turn, brand image and perceived value significantly influence purchase intention and serve as important mediators in the relationship between sustainable marketing and purchase intention. Regarding moderation effects, social influence significantly moderates the relationship between brand image and purchase intention, while its moderating effect on the relationship between perceived value and purchase intention is not supported. These findings provide empirical evidence on the mechanisms through which sustainable marketing shapes consumer behavior and offer practical implications for organizations in developing effective sustainability-oriented marketing strategies targeting Generation Z consumers.
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Leadership Dynamics in Human-in-the-Loop Security Models for General-Purpose AI Systems: Implications for Workforce and Technological Transformation
The rapid diffusion of artificial intelligence as a general-purpose technology is fundamentally reshaping organizational structures, leadership roles, and workforce capabilities. Despite growing interest in AI-driven transformation, limited research integrates human-centered design perspectives with strategic capability development to explain how organizations adapt to Human–AI collaboration. This study addresses the gap by reviewing and conceptually integrating Sociotechnical Systems Theory and Dynamic Capabilities Theory to examine the role of Human-in-the-Loop mechanisms in organizational transformation. Data has been collected using structured pre-coded research instrument from 15 senior executives (5 senior executives from each industry) and 148 mid-level employees during April 2025 – September 2025. This study contributes to the existing literature by analyzing the effectiveness of human-in-the-loop security models in the organizations in the context of leadership skills, employee engagement, and ethical challenges in implementing AI tools within day-to-day activities. Organizations may need to entrench HITL practices into leadership development programs, and performance evaluation.
Developing Servant Leaders in Manufacturing: AMixed-Methods Study of Leadership Growth andFollower Perceptions
This study explores the need for and development of servant leadership within a U.S.-based manufacturing context through a mixed-methods approach integrating follower-based assessment and qualitative inquiry. Grounded in servant leadership theory, particularly the centrality of listening as a defining leadership disposition (Greenleaf, 1977), the research investigates how leadership behaviors are practiced and experienced by those being led. Participants were identified as emerging leaders by senior leadership and enrolled in a three-month leadership development program designed to cultivate relational and servant leadership competencies. Behaviors were measured using the Servant Leadership Questionnaire (Liden et al., 2008), completed by each leader’s direct reports at two time points: prior to and following the training. This approach provided follower-based evaluations across key dimensions, including listening, empathy, and conceptualization. To deepen these findings, semi-structured interviews were conducted with a purposive sample of participants, focusing on their self-perceptions, leadership challenges, and developmental trajectories. Findings indicate measurable growth in follower-perceived servant leadership behaviors, alongside a notable shift in leaders’ self-awareness. Listening emerged as both a developmental gap and a critical area of improvement. Qualitative data suggest that structured reflection and one-on-one coaching conversations were instrumental in translating leadership concepts into consistent, observable practices. This study contributes to leadership development research by demonstrating the effectiveness of integrating follower feedback and reflective dialogue, with implications for manufacturing and other industrial, operations-based organizations.
Scouting Engaging Influencers to Recommend Brands for S-Commerce Repurchase Success in Sustainability
This study examines the role of social media influencers and consumer engagement in predicting repurchase behavior on a social commerce (s-commerce) platform. Addressing research gaps in cultural, platform, and methodological contexts, the research analyzes real transactional data collected from the largest influencer-driven s-commerce group-buying platform in Taiwan. Using the AMOS 29 Structural Equation Program and a consumer engagement perspective, the study investigates how Facebook-related influencer and consumer engagement factors predict s-commerce repurchases. The results indicate that an influencer’s Facebook follower count is positively associated with s-commerce electronic word-of-mouth (eWOM) interactivity, whereas the number of Facebook posts does not significantly affect interactivity. In addition, both behavioral engagement and emotional engagement on Facebook are shown to be indicators of s-commerce eWOM interactivity. The results further demonstrate that s-commerce eWOM interactivity positively affects repurchase behavior among consumers. Finally, the study finds that limited-time sales negatively moderate the relationship between s-commerce eWOM interactivity and repurchase behavior. The study contributes to influencer marketing and social commerce literature by using real transactional data from a Taiwanese social commerce environment and extends understanding of how engagement factors influence repurchase outcomes in online group-buying platforms.
What Shapes Gender Gaps in Entrepreneurship? Entrepreneurial Ecosystem Conditions and Gender Differences in Activity and Perceptions
Women’s entrepreneurial participation contributes to economic activity, job creation, and diversity in products, markets, and organisational forms. Yet research has largely examined women’s entrepreneurship or women’s and men’s activity separately, offering limited insight into how entrepreneurial ecosystems shape gender gaps in activity and perceptions. Drawing on a gendered institutions perspective, we argue that, by structuring access to finance, public support, education, infrastructure, and cultural legitimacy, ecosystem conditions may narrow some gaps while leaving others unchanged or widening them. We combine Global Entrepreneurship Monitor Adult Population Survey and National Expert Survey data for 106 countries from 2009 to 2021, yielding 686 country-year observations. Country and year fixed-effects models with country-clustered standard errors capture within-country changes over time. Results reveal divergent associations. Government programmes are associated with a smaller opportunity-perception gap, whereas favourable entrepreneurial finance is associated with a larger gap. Physical infrastructure is marginally associated with a smaller early-stage entrepreneurial activity gap. Supplementary analyses show that entrepreneurship education is positively associated with women’s entrepreneurial activity, while finance and education are associated with higher opportunity perception among women. However, these gains do not consistently translate into smaller gaps relative to men, and opportunity perception does not mediate the relationships of finance and education with women’s entrepreneurial activity. These findings shift attention from conditions that merely increase women’s entrepreneurial activity to those that reduce the gap between women and men. Gender gaps are multidimensional, and broad ecosystem improvements may be insufficient unless institutional arrangements target barriers underlying activity, opportunity, capability, and fear-of-failure gaps.
Integrating Spiritual Values in Business Management: A Framework for Sustainable Organizational Change
This study explores the integration of spiritual values into business management as a strategic approach to supporting sustainable organizational change, ethical leadership, and employee well-being. While workplace spirituality has received increasing scholarly attention, there remains a lack of structured frameworks that translate spiritual values into actionable managerial practices. To address this gap, the research develops the Spiritual Values Integration Model (SVIM), a conceptual framework designed to guide organizations in embedding spiritual values into their change management processes. The study adopts a qualitative research design combining a systematic literature review with comparative case-based analysis of organizations that have implemented value-driven management practices. The findings demonstrate that spiritual values - including integrity, compassion, purpose, authenticity, and social responsibility- strengthen organizational resilience, improve employee engagement, support ethical decision-making, and contribute to long-term performance sustainability. In addition, the results highlight several indirect economic benefits associated with spiritual-value-based management, including improved talent retention, enhanced innovation capacity, stronger stakeholder relationships, and reduced organizational resistance to change. The proposed SVIM framework provides a structured seven-stage implementation pathway that aligns leadership commitment, organizational culture, and employee participation with strategic transformation processes. The study contributes to the literature on workplace spirituality and organizational change by offering a practical integration model applicable across diverse organizational contexts. The findings suggest that spiritual values can function not only as ethical principles but also as strategic resources supporting adaptive and resilient management systems.
Shareholder Activism and CEO Turnover in Private Equity–Backed Firms: Leadership Alignment and Executive Cohesion
Private equity (PE) ownership often combines intensified performance cycles, making leadership alignment and cohesion critical for the success of the organization. Any disruption in governance and strategy execution such as CEO replacement may be a serious risk to business continuity. Building on Upper Echelons Theory (Donald C. Hambrick & Phyllis A. Mason, 1984), PE governance research (Steven N. Kaplan & Per Strömberg, 2009), hedge fund activism evidence on governance intervention effects (Lucian A. Bebchuk, Alon Brav & Wei Jiang, 2015), and CEO succession process work on post succession executive turnover (Wei Shen & Albert A. Cannella Jr., 2002), this proposed study examines the dynamics of leadership alignment and executive cohesion under repeated CEO turnover within a single PE holding period. The empirical setting is a longitudinal case study of a PE-backed firm that experienced three CEO transitions during one year. Using qualitative process tracing, executive interviews, board documentation, and reconstructed performance trajectories, the analysis will track how each transition reshapes strategic direction, leadership team integration, and cultural coherence, drawing on team management behavioral integration research (Michael H. Lubatkin, Zeki Simsek, Yan Ling & John F. Veiga, 2006). The study expects three recurring inflection points: (1) strategic reorientation shocks that disrupt shared priorities, (2) fragmentation risks driven by shifting authority and loyalty realignments, and (3) short cultural realignment windows that enable recalibration but also heighten uncertainty. The paper will develop the Leadership Alignment Under Activist Turnover (LAAT) framework, specifying phases of alignment disruption and recovery and identifying governance practices such as role-boundary clarity, consistent transformation narratives, and cadence-based integration routines, that may mitigate cohesion loss. The contribution is to connect governance-level intervention logics with level leadership dynamics in high-paced CEO turnover contexts.
Exploring the Advertising Effectiveness of Podcasts: a Congruence Theory Perspective
Podcast listenership and influencer activity have grown at a remarkable pace, drawing increasing interest in podcast-based advertising. Despite the clear commercial benefits this presents for content creators and platform operators, the academic literature offers little guidance on how to maximize the impact of such advertising. This study addresses that gap by applying congruence theory as its theoretical lens, investigating how two distinct forms of congruence shape audience responses to podcast advertisements, specifically their perceived advertising irritation and persuasiveness, and how these reactions subsequently drive advertising attitudes and purchase intentions. To explore these relationships, a conceptual model was developed and tested using data gathered through an online survey. Structural equation modeling, conducted via SmartPLS, was employed to analyze the data. Findings reveal that congruence cues embedded in podcast advertising, namely the alignment between podcast content and advertisement content and between the podcaster's image and the advertised product, positively influence how audiences perceive both advertising irritation and persuasiveness. Furthermore, both of these perceptions were confirmed as significant predictors of advertising attitudes and purchase intentions. These findings offer nuanced insight into the psychological and behavioral mechanisms through which podcast advertising operates, shedding light on strategies that can enhance its overall effectiveness. From a scholarly standpoint, this research extends the online advertising literature into the relatively underexplored domain of podcasting, while also offering actionable takeaways for digital marketing practitioners seeking to optimize their podcast advertising strategies.
AI Adoption for Business Leaders: Why Practical Strategy Beats Technology Hype
Artificial intelligence is reshaping the competitive landscape for businesses of every size, yet adoption among small and medium-sized enterprises remains patchy, poorly planned, and frequently ineffective. This presentation draws on practitioner experience across multiple business sectors, supported by findings from an ongoing AI Readiness Assessment conducted with UK business leaders, to argue that the primary barrier to successful AI adoption is not technological capability but leadership clarity. Many organisations approach AI as a technology project rather than a strategic business decision. The result is investment without direction, tool adoption without integration, and enthusiasm without measurable return. This paper proposes a practical leadership framework for AI adoption built around four interdependent pillars: strategic intent, organisational readiness, people and culture, and governance. Drawing on real-world case examples and structured responses from business leaders across UK industries, it identifies the most common failure points in AI adoption and offers a replicable model for leaders seeking to embed AI as a sustainable business capability rather than a short-term experiment. The paper also examines the role of the leader as the critical enabler or inhibitor of AI adoption, and considers how leadership development must evolve to equip executives with the confidence and competence to make informed AI decisions. The central argument is clear: AI is only a threat when your competitors are using it and you are not. The antidote is not more technology, but better leadership thinking.
Navigating Complexity in Project-Based Organizations: Artificial Intelligence as a Systemic Driver of Managerial Decision-Making
Contemporary projects increasingly operate as complex adaptive systems in which volatility, interdependence, uncertainty, and multiple stakeholder interests challenge conventional planning and control approaches. This study examines how artificial intelligence (AI) reconfigures complexity in project management and reshapes managerial decision-making, governance, and leadership. A qualitative meta-aggregative synthesis was conducted following PRISMA and Joanna Briggs Institute guidelines. The evidence base comprised 77 peer-reviewed studies on project complexity and a complementary corpus of 41 studies on AI-supported managerial decisions published between 2020 and 2025. The findings identify four cumulative conceptual generations and five interrelated dimensions of complexity: structural, dynamic, systemic, cognitive, and sociopolitical. Complexity emerges primarily from the interaction of uncertainty, interdependence, and volatility rather than from isolated technical difficulties. AI reduces first-order uncertainty by expanding data-processing, forecasting, and risk-analysis capabilities; however, it simultaneously creates second-order uncertainty associated with algorithmic opacity, bias, explainability, accountability, and shifts in organizational power. Consequently, AI should be understood not merely as an efficiency tool but as an endogenous systemic agent that transforms project governance and managerial authority. The study proposes that effective leadership in complex project environments requires hybrid intelligence, adaptive governance, collective sensemaking, organizational learning, and critical algorithmic literacy. These capabilities enable managers to balance analytical automation with contextual judgment, ethical responsibility, and continuous adaptation.
Stage-Specific Generative AI Disclosure: Mention, Planned Adoption, and Implementation
As generative AI diffuses across industries, corporate disclosure becomes a strategic signal not only to investors, but also to regulators, employees, and product-market rivals. A central measurement problem is that firms often use similar AI language to communicate very different realities, including broad narrative positioning, forward-looking commitments, and claims of operational deployment. This paper argues that treating these statements as equivalent can distort both managerial inference and capital-market interpretation. We therefore construct stage-specific disclosure measures that separate mention, planned adoption, and implementation in U.S. 10-K filings, rather than relying on undifferentiated keyword intensity. Methodologically, we fine-tune a BERT-based classifier for sentence-level stage classification and then aggregate predicted stages to the filing level. The classifier attains 87.3% accuracy and 86.9% macro-F1 on a held-out test set, supporting scalable measurement in a large panel. We then estimate OLS regressions of abnormal stock price on disclosure composition, controlling for firm characteristics, year and industry fixed effects. Planning language is associated with significantly lower CAR, while implementation language is positive in point estimates but imprecisely estimated. Cross-industry patterns illustrate construct validity: information technology combines high GenAI intensity with high action-oriented disclosure, whereas finance exhibits broad GenAI discussion but comparatively low action shares. Overall, the evidence shows that AI disclosure is multi-dimensional and that composition, not only volume, is crucial for evaluating disclosure credibility, execution risk, and market response.
Unlocking the Green Transition: Open Innovation as an Econometric Framework for Efficient European Eco-Innovation
Eco-innovation is a central pillar for driving environmental sustainability and economic competitiveness under the European Green Deal. However, traditional closed innovation approaches frequently fail under the weight of high capital expenditure, systemic complexity, and the multidisciplinary knowledge demands required for clean technology breakthroughs. Integrating the Knowledge-Based View (KBV) and the Natural-Resource-Based View (NRBV), this paper formulates a panel econometrics framework to model European Eco-Innovation Efficiency (EIE) across EU Member States. We propose a theoretical two-stage stochastic frontier specification that incorporates inbound knowledge flows, collaborative network depth, and institutional regulatory stringency to isolate the mechanics of eco-innovation performance. Our structural model yields a key theoretical finding: Open Innovation operates non-linearly on Eco-Innovation Efficiency, where institutional regulatory stringency acts as a crucial moderating catalyst. While open inbound collaboration accelerates knowledge recombination, its efficacy is bound by search friction and coordination costs. Strict environmental policy stringency shifts the efficiency frontier upward by standardizing cross-organizational goals, mitigating opportunistic behavior, and directing collaborative networks toward high-impact, compliance-oriented green technologies. These findings demonstrate that open innovation ecosystems, when coupled with targeted regulatory drivers, provide the necessary structural framework to eliminate systemic inefficiency and optimize clean technology deployment across the European Union.
AI Strategic Repositioning in the Era of Generative AI: Evidence from Strategic Portfolios and Strategic Transitions of Korean Firms
The emergence of Generative Artificial Intelligence (GenAI) has transformed not only how firms deploy digital technologies but also how they prioritize strategic initiatives. While prior research has primarily focused on AI adoption, investment, and capability development, relatively little attention has been paid to how firms reposition their AI strategies over time. This study examines the evolution of corporate AI strategies in the context of the GenAI era using public disclosure data from Korean listed firms. A total of 73,596 AI-related sentences were extracted from 7,666 corporate disclosure documents and classified into eight strategic categories: Data Analytics AI, Operational AI, Product-Service AI, Scientific R&D AI, Customer AI, Financial AI, Generative AI, and Governance AI. Based on these classifications, 6,320 firm-year AI strategic portfolios were constructed and analyzed in terms of strategic diversification, dominant strategies, and strategic transitions. The results show that AI strategic portfolios have become increasingly diversified over time, with a significant acceleration after the emergence of GenAI. More importantly, firms exhibit systematic strategic transitions from broad and general AI positioning toward more specialized domains, particularly Financial AI, Product-Service AI, and Scientific R&D AI. These findings suggest that GenAI functions not merely as a technological innovation but as a catalyst for strategic repositioning by reshaping firms’ strategic attention and resource allocation priorities. This study contributes to the literature by shifting the focus from AI adoption and capability development to the dynamic evolution of AI strategy portfolios. It also provides evidence that AI-related strategic change in Korean firms is characterized by strategic repositioning rather than simple diversification.
From Sensemaking to Sensebecoming: How Institutional Contexts Shape Generative AI Use in Higher Education
The rapid diffusion of generative artificial intelligence (AI) is transforming higher education, yet little is known about how students and staff make sense of these technologies and incorporate them into learning practices. Drawing on sensemaking and sensegiving theory, this study examines how actors construct meaning around generative AI and how these interpretations evolve into emerging practices. Using a comparative qualitative design across traditional universities and private tertiary institutions, we explore how institutional contexts shape the cues that actors draw upon to interpret AI. Our findings reveal distinct sensemaking trajectories. In traditional universities, generative AI is framed through epistemic concerns, academic integrity, and disciplinary norms, producing cautious experimentation and contested interpretations. In contrast, actors in private tertiary institutions interpret AI through employability, efficiency, and skill development, leading to more instrumental and pragmatic adoption. These differences shape divergent sensegiving dynamics, with traditional universities emphasizing boundary-setting while private institutions actively promote AI-enabled learning. We theorize these processes as sensebecoming, whereby actors move from interpreting generative AI to developing evolving norms and practices for its use. This study extends sensemaking research by showing how institutional contexts shape the transition from interpretation to practice during technological disruption.
Cultural Value Communication in Creative Economy Products: A Second-Order Measurement Model in the Context of Thai Floral Perfume Branding
This study aims to develop and validate the structural validity of a measurement model for cultural value communication in the context of Thai floral perfume products. It conceptualizes cultural value communication as a reflective second-order construct comprising four dimensions: consumption value, brand storytelling, authenticity, and symbolism and visibility. Data was collected from 400 consumers and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the quality of the measurement model at both the sub-component and higher-level components. The results indicate that the first-order measurement model demonstrated satisfactory reliability and convergent validity. Cronbach’s alpha values ranged from 0.780 to 0.861, composite reliability values ranged from 0.872 to 0.906, and AVE values ranged from 0.687 to 0.706. The HTMT values among the first-order dimensions ranged from 0.631 to 0.707, indicating adequate discriminant validity across the four dimensions. For the second-order construct, cultural value communication showed satisfactory reliability and convergent validity, with Cronbach’s alpha = 0.848, composite reliability = 0.898, and AVE = 0.687. In addition, the bootstrapping results confirmed that all four first-order dimensions significantly reflected the higher-order construct, with coefficients ranging from 0.959 to 0.995 and statistical significance at p < .001. These findings support the empirical validity of cultural value communication as a reflective second-order construct in the context of Thai floral perfume products. This study presents a cultural value communication measurement scale that explains the roles of storytelling, authenticity, consumption value, and symbolism in elevating Thai products into meaning-based offerings.
When AI Feels Fair: The Distinct Roles of Procedural and Distributive Justicein Reducing Organizational Dehumanization under AI-Enabled HRM
The use of AI-enabled Human Resource Management (AI-HRM) has expanded rapidly as organizations seek to improve the efficiency and fairness of HR practices through greater objectivity, consistency, and reduced bias. However, concerns remain regarding whether algorithm-based decision-making may contribute to organizational dehumanization. Drawing on Organizational Justice Theory, this study examines the mediating roles of procedural justice and distributive justice in the relationship between AI-HRM and organizational dehumanization. Using employee reviews collected from Glassdoor, we developed organization-level measures of AI-HRM, procedural justice, distributive justice, and organizational dehumanization through a hybrid text-mining approach that combines S-BERT semantic similarity analysis with theory-driven keyword dictionaries. The results show that AI-HRM is positively associated with both procedural justice and distributive justice, with a stronger effect on procedural justice. Furthermore, both justice dimensions are associated with lower levels of organizational dehumanization, although distributive justice exhibits a substantially stronger effect than procedural justice. Mediation analyses reveal significant indirect effects of AI-HRM on organizational dehumanization through both justice dimensions. These findings suggest that AI-HRM primarily enhances employees’ perceptions of fair procedures by increasing consistency, transparency, and objectivity in decision-making, while fair outcomes play a more critical role in preserving employees’ sense of human dignity and reducing perceptions of organizational dehumanization. The study contributes to the AI-HRM literature by identifying organizational justice as a key mechanism linking AI-HRM to employee perceptions of dehumanization.
Beyond Technology: a Human Systems Framework for Diagnosing Organizational Readiness in AI Adoption
While the technical hurdles of AI adoption are steadily being cleared, organisational failure rates remain stubbornly high. This disconnect stems from a persistent framework bias: implementation programmes continue to prioritise "can the system work?" over "will the human system let it?". This study addresses that gap. Drawing on qualitative data from fifteen cross-sector knowledge workers, it presents the HuSAT (Human System for Adaptive Trust) framework. A five-condition diagnostic model mapping the human system factors that determine whether AI deployment produces calibrated trust or entrenched resistance. The central finding is that professional identity functions as a master variable. When AI threatens a user's sense of professional self, they actively subvert adoption by resorting to shadow manual processes, sandbagging, and self-exclusion from digital workflows, regardless of technical literacy or organisational mandate. Identity threat is not a soft concern; it is the primary mechanism through which technically sound implementations fail. The research makes three contributions. First, it distinguishes calibrated trust from binary adoption as the appropriate success metric for AI integration. Second, it reframes parallel running (widely treated as a technical precaution) as a psychological safety mechanism. Third, it identifies assumption transparency and co-creation as the primary conditions under which trust builds incrementally rather than being granted at deployment. The HuSAT framework offers practitioners a structured diagnostic for identifying human-centric failure points in finance functions undergoing intelligent automation and a more honest account of what successful AI adoption actually requires.
Are Boundaryless Careerists a Breed apart from Organization? Insights from South Korea and United States
The purpose of this paper is to examine the paths through which boundaryless career attitudes lead to knowledge sharing through self-regulated learning. Based on social capital theory, we contended that boundaryless careerists enhance career competencies and share them in the form of knowledge. Utilizing mixed samples in South Korea and the United States, we found that among the sub-dimensions of boundaryless career attitudes, boundaryless mindset led to knowledge sharing through self-regulated learning, while organizational mobility preference demonstrated both a significant direct and indirect effect on knowledge sharing through self-regulated learning, with both paths operating in a negative direction. In this intra-organizational mechanism, we also discovered that nationality (South Korea vs. the United States) had a significant moderating effect. By unpacking the heterogeneous nature of boundaryless career attitudes and identifying how national context shapes the translation of individual career orientations into collective organizational outcomes, this study offers novel theoretical and practical insights into the role of contemporary career orientations in organizational knowledge processes. Further implications and future directions are discussed.
From “Passive Adaptation” to “Proactive Reshaping”: A Qualitative Exploration of the Work Values and Career Expectations of Post-00s Interns
Against the backdrop of higher education massification, structural economic transformation, and intensifying credential inflation in China, the transitional landscape for the youth demographic entering the labor market is undergoing a systematic reconstruction. As the vanguard of the contemporary workforce, the Post-00s (Generation Z) introduces distinct work values and career expectations that challenge traditional, top-down bureaucratic employment relationships. This study utilizes a qualitative research design to explore the psychological contracts, work values, and career navigation strategies of Post-00s interns, illuminating their agency-driven adaptation mechanisms when confronting credential devaluation and workplace uncertainty. Through semi-structured interviews conducted via purposive and snowball sampling within business hubs of Shenzhen city, the narrative data were systematically analyzed using grounded theory coding procedures. The empirical findings reveal three primary themes. First, Post-00s interns reject traditional relational loyalty, reconfiguring the psychological contract around developmental symbiosis, immediate mutual value, and psychological well-being; when expectations are breached, they actively renegotiate boundaries or alter workflows instead of executing passive withdrawal. Second, they naturally conceptualize organizations as Complex Adaptive Systems rather than rigid hierarchies, utilizing informal networks and digital collaboration tools to bypass bureaucratic bottlenecks and optimize workflows. Third, driven by macro-level hyper-competition, these individuals strategically use proactivity as a calculated mechanism for positional capital accumulation and career navigation to maximize returns on their investments. Consequently, this study concludes that contemporary human resource management frameworks must undergo a structural upgrade from top-down compliance into agile enablement systems, leveraging the proactive tendencies of the younger workforce as strategic assets for organizational innovation and long-term resilience.
Student Managed Investment Fund Participation and Career Readiness in Business Education
Student run investment clubs represent an intensive form of experiential learning that integrates academic knowledge practical skill development and professional socialization within business education. Drawing on experiential learning theory and the high impact practices framework this study examines how participation in a student managed exchange traded fund portfolio influences multidimensional college adjustment and early career outcomes. College adjustment is conceptualized using the Student Adaptation to College Questionnaire which measures academic adjustment social adjustment personal emotional adjustment and institutional attachment (Baker & Siryk, 1984 1989). Data are being collected through an Institutional Review Board approved mixed methods design at a public university in the Middle Tennessee region. Quantitative survey data from current club members assess adjustment across SACQ domains while qualitative interviews with alumni one to five years post-graduation examine perceived career readiness professional identity development and employment trajectories. Experiential learning theory suggests that sustained engagement in authentic financial decision making promotes deep learning skill transfer and self-efficacy (Kolb, 1984) while high impact practice research predicts gains in persistence engagement and post-graduation success through intensive collaborative environments (Kuh, 2008). The study contributes to management education and talent development research by providing evidence on whether student managed investment funds function as a high impact practice that enhances student success and workforce preparation. Findings are expected to inform faculty advising co-curricular program design and institutional strategies aimed at improving career readiness and long-term professional outcomes for business graduates.
Always Connected Social Media Notifications and Managerial Control in the Generation Z Workplace
The always connected nature of contemporary work has intensified the presence of social media notifications and created new forms of communicative demands that compete with sustained attention and task focus. This study examines how social media induced fear of missing out compulsive checking multitasking interruption overload and procrastination influence perceived productivity among Generation Z employees and whether managerial communication can mitigate these effects. Data are being collected through an Institutional Review Board approved survey using validated measurement items adapted from the Social Media Use at Work measurement model which captures fear of missing out compulsive use work performance decrement and procrastination behaviors in organizational settings (Tandon et al., 2021). Interruption overload and psychological transition after digital interruptions are measured using established enterprise social media scales that assess the cognitive and energy costs of frequent workflow disruptions (Luqman et al., 2021). Managerial boundary setting and communicative role clarity are operationalized using work related social media communication measures that conceptualize social media activity as a form of communicative labor shaping employee responsibilities and performance expectations (Pekkala, 2021). By integrating these measurement approaches the study develops a multidimensional model of digital distraction and managerial control in notification rich work environments. The study contributes to management and organizational behavior scholarship by identifying how digitally mediated communication reshapes attention regulation and by testing whether clear managerial expectations improve focus and productivity. The findings are expected to inform leadership communication digital workplace policy and the design of attention supportive work systems for the Generation Z workforce.
Alcohol Motives and Professional Identity Development in Business Students
This study examines the relationship between alcohol motives and the development of professional identity among undergraduate business students. Professional identity emerges prior to workforce entry and is shaped by socialization processes, peer norms, and institutional expectations (Ashforth et al., 2021; Jackson, 2017). Drawing on social identity theory, which explains how group belonging and perceived legitimacy influence behavior and self-concept (Bliuc et al., 2011), this research examines whether alcohol related motives are associated with perceptions of professionalism, employability, and comfort in career-relevant settings. Alcohol use functions as a visible social behavior through which belonging and social fit are negotiated in emerging adulthood (MacLean, 2016; Brooks et al., 2015), yet its role in pre-professional identity formation within business education remains underexplored. Data were collected through an IRB approved survey administered in a college of business at a public university in the Middle Tennessee region. The instrument incorporates selected items from the Young Adult Alcohol Motives Scale to measure coping, social, enhancement, and interpersonal comfort motives, alongside original measures of professional identity, perceived career readiness, and professional image management. By integrating professional identity theory with social identity theory and research on alcohol motives, the study extends talent development and professional socialization scholarship into the pre-employment stage. The findings are expected to have practical implications for management education, leadership development, and organizational onboarding by improving understanding of how Generation Z business students navigate social norms as they construct a professional self.
Technology Adoption and Informal Entrepreneurship: A Bibliometric Analysis of Web of Science
The emergence of information technology in the 21st century has significantly transformed human interactions and business operations. Smartphones and handheld smart devices have pushed the boundaries of entrepreneurship, enabling business expansion and market access on a global scale (Balachandran & Sakthivelan, 2013). Tamilmani et al. (2021) argue that technology adoption is a well-established research domain within the information systems (IS) literature, with ongoing investigations into the factors influencing individuals' acceptance and use of new information technologies (IT). In the context of informal entrepreneurship, technology adoption has facilitated business operations by enabling entrepreneurs to circumvent bureaucratic barriers and lengthy legal procedures associated with business formalization. Williams and Nadin (2010, p.363) define informal entrepreneurship as “the involvement of individuals actively engaged in starting a business or managing an enterprise that is less than 42 months old, participating in the paid production and sale of goods and services that are legitimate in all respects except for being unregistered or hidden from the state for tax and/or benefit purposes.” As technology adoption and informal entrepreneurship continue to gain academic and policy attention, it is crucial to understand how digital tools impact informal business operations. This study employs a bibliometric analysis using the Web of Science (WoS) database to systematically map the intellectual structure of research on technology adoption in informal entrepreneurship. Santos and Ferreira (2017) claim that Web of Science registered its first publication in 1994. A preliminary search in WoS has revealed over 10,000 articles related to this domain. The study targets publications (Articles and Conference proceedings) from 2000 to 2024, with data sourced exclusively from articles indexed in the Web of Science. Exclusion and inclusion criteria have been used for the search. By leveraging bibliometric tools such as CiteSpace, RStudio, VOSviewer, and Biblioshiny, this study conducts performance analysis, co-authorship network analysis, and thematic mapping to identify key research trends, influential scholars, and emerging themes. Drawing on existing literature and bibliometric methodologies, the review identifies key trends, theoretical foundations, and research gaps. The findings aim to enhance understanding of how digital innovation influences informal entrepreneurial activities and to inform future research and policy development in this emerging area.
Green Signal and Global Sales: The Impact of Environmental Accounting Disclosure on Export Performance of Small Cap Firms in South Africa
Small and medium enterprises are an essential part of any economy as a result of their contributions to the economic output. However, the export performance of SMEs, especially in developing countries, is limited by environmental regulations enacted to achieve sustainability goals due to compliance costs. Moreover, there is a paucity of studies on how environmental disclosure practices impact the export performances of SMEs. Hence, this study investigates the effect of environmental accounting disclosure on the export performance of 15 small-cap companies in South Africa. Using panel regression analysis, the result showed that environmental accounting disclosure (EAD) exerts a significant and negative impact on export revenue. Also, firms’ size (TA) has a direct and significant relationship, while market capitalization and leverage variables have no significant effect on export performance. In addition, the effect of exchange rate is positive and significant on export revenue. This study concludes that the level of environmental accounting disclosure by SMEs is significant in improving the export performance of SMEs in South Africa. Therefore, there is a need for a supportive policy framework to alleviate the financial burden for environmental transparency to bolster the international competitiveness of small-cap businesses.
A Cross-national Comparison of Click-through Rates for AI Overview Keywords
The growth of AI Overviews in Google Search has prompted questions about whether searcher click behaviour varies across national markets. Understanding cross-national click-through rate (CTR) differences is critical for global ecommerce brands managing search engine optimisation (SEO) strategies across multiple regions. This study examines whether CTR for AI Overview keywords differ significantly between US and UK searchers, after controlling for keyword difficulty, keyword intent, and keyword competition. A cross-sectional analysis was conducted on 1,303 keyword-level observations drawn from 18 ecommerce websites tracked across both markets during the month of December 2025. The ANCOVA regression analysis documented that US keywords exhibited significantly higher AI overview CTR compared to UK keywords (B = 0.272, p < .001, partial η² = .033). navigational and transactional intent keywords also yielded significantly higher CTR than informational keywords. Keyword difficulty and competition were not significant predictors. US searchers demonstrate consistently higher CTR for AI Overview keywords than their UK counterparts, independent of keyword characteristics. These findings have implications for how global ecommerce brands should interpret and benchmark CTR across markets.
Unique Dynamic Capabilities for Technology Adoption
Digital transformation allows companies to adopt new technologies, enhance efficiency, and stay competitive. However, technology advancements also pose uncertainty that urges organizations to make essential changes. Adopting new technologies requires building dynamic capabilities (DCs) to foster innovation and adaptability (Teece, Pisano, & Shuen, 1997). DCs framework is one of the prominent theories in strategic management. It refers to an organization’s ability to sense, seize, and transform opportunities and threats in rapidly changing environments (Teece, 2007). The integration of DCs framework into knowledge management, managerial capabilities and digital transformation theories results in novel concepts of dynamic managerial capabilities DMCs (Hefta and Martin, 2015), dynamic knowledge management DKM (Li et al., 2025), as well as different microfoundations of DCs. The development of DCs generates valuable findings, yet they remain general and not timely with the context of technology advancements. This research aims to further explore concepts related to DKM and DMCs, specifically focusing on sensing capabilities and managerial cognition - their construal levels, moderated by organization design. The research employs qualitative approach, interviewing technology leaders, project managers, HR, consultants and operational staff in three selected Nordic organizations. Findings of the research contribute to the development of DCs framework with technology adoption context, coherency in managerial construal level impacts, and a shift in perspectives from routine-based practices and efficiency to the orchestration of collaboration and dynamic activities. In practice, it provides guidance for leaders to cultivate DCs that allow organizations to embrace technology trends and sustain long-term viable performance.
Linking Paradoxical Safety Leadership and Employee Safety Behaviors through the Lense of Affective Events Theory: a Moderated Mediation Model
Paradoxical leadership has recently emerged as an important leadership style in organizational behavior. However, despite its growing importance, the role of paradoxical leadership in workplace health and safety largely remains unexplored. To fill this gap, the current study explores how paradoxical safety leadership affects employee safety behaviors via harmonious safety passion. Moreover, drawing upon affective events theory, the study unpacks the combined effects of harmonious safety passion safety internal locus of control on employee safety behaviors. Following the survey method, data were collected from 240 healthcare workers employed in diverse healthcare sectors across Pakistan. AMOS and SPSS were used to establish the reliability and validity of the collected data. The findings revealed that paradoxical safety leadership positively and significantly improves harmonious safety passion of healthcare workers which in turn leads to better safety behaviors i.e. prosocial and proactive safety behavior. The results also found moderating role of safety internal locus of control between harmonious safety passion and safety behaviors. This study offers valuable insights and practical implications for policymakers to guide policies and interventions aimed at fostering safety behaviors in healthcare sectors. Policymakers and healthcare providers should promote safety-oriented leadership style by empowering healthcare professionals to effectively navigate safety protocols and behaviors. These efforts will strengthen harmonious safety passion among employees enhancing overall safety practices in healthcare settings. The study also addresses limitations along with future research directions.
Regime-Switching Prediction of Intraday Equity Trading Outcomes:A Hidden Markov Model Approach for Semi-Automated Scalping and Swing Strategies
Retail and independent traders increasingly rely on semi-automated systems that combine discretionary judgment with rules-based technical signals, yet little empirical research examines whether the market conditions underlying a trade, also known as its latent “regime,” can be systematically identified and used to predict trade outcomes before entry. This dissertation applies the concept of “Hidden Markov Models (HMMs)” to a longitudinal dataset of personal intraday and swing equity trades, using a structured technical framework (Smart Money Concepts, VWAP, EMA, RSI, and MACD) as the observable signal layer from which latent market states are inferred. The study treats each trade’s surrounding price and indicator behavior as an emission sequence, fits an HMM to recover hidden regime states (e.g., trending, ranging, high-volatility, low-volatility), and tests whether regime classification at the time of entry improves the predictability of trade outcome (win/loss, magnitude, and risk-adjusted return) relative to indicator signals alone. Using single-account, semi-automated equity trading data collected over 27 months, this research contributes: (1) an applied methodology for retail-scale regime detection without institutional-grade data infrastructure; (2) an empirical assessment of whether regime-aware trade filtering measurably improves outcome prediction; and (3) a case-study framework other independent and semi-automated traders can replicate on their own trade logs. Findings are framed as a single-subject, proof-of-concept study rather than a population-generalizable trading system, with explicit discussion of the tradeoffs this design choice implies for external validity.
When Does Employee Wellbeing Drive Firm Growth? Burnout Prevention Climate and the Returns to Innovation Investment
Employee wellbeing has been recognized as a strategic resource for organizational success, yet prior research has reported mixed findings regarding its impact on firm performance. While some studies suggest that employee wellbeing enhances productivity and organizational outcomes, others find limited or inconsistent effects. These conflicting findings raise an important question regarding the conditions under which wellbeing creates economic value. Drawing on psychological safety theory, dynamic capabilities, and complementary assets perspectives, this study examines whether a burnout prevention climate functions as a complementary organizational capability that enables firms to realize the returns from innovation investments. Using employee reviews from Glassdoor matched with Compustat financial data, this study focuses on startups and mid-sized growth-oriented firms rather than large established corporations. Burnout prevention climate is measured through text-based analysis of employee reviews, and its relationship with future sales growth is examined using panel fixed-effects models. The moderating role of R&D intensity is also investigated. The results show that burnout prevention climate has only a limited direct effect on future sales growth. However, its positive impact becomes significantly stronger as R&D intensity increases. Johnson–Neyman analysis further reveals that the effect is significant only among firms with relatively high levels of R&D investment. These findings indicate that employee wellbeing does not uniformly translate into organizational growth; rather, it generates economic value when combined with innovation-oriented strategic investments. This study identifies innovation intensity as a critical boundary condition of the wellbeing–performance relationship and conceptualizes burnout prevention climate as a complementary organizational capability that helps firms convert innovation investments into growth outcomes. By focusing on startups and mid-sized firms, the study extends existing wellbeing research beyond large corporations and provides new evidence on the strategic value of organizational wellbeing in growth-oriented firms.
Achieving Sustainable Success in Japan's Mobile Gaming Market Investigation by Mixed-Methods
Japan's mobile gaming market has the world's highest in-app purchase rates, yet many games shut down prematurely and numerous companies report declining revenues. This study examines conditions for sustainable success across three levels—player, game, and company—using factor analysis of a 500-player survey, Qualitative Comparative Analysis (QCA) of 104 games across 18 companies, and case studies spanning 2014–2023. Six purchase motivation factors and seven churn factors have been identified by factor analysis. Critically, high-revenue motivations such as seeking social status, collecting characters through random reward mechanisms, and enhancing game efficiency showed positive correlations with churn risk (r = .314–.376). By contrast, motivations rooted in playing with friends, supporting developers, and leisure showed negligible churn correlations, suggesting more sustainable monetization potential. QCA identified two success patterns for long-term mobile game operations. Small-to-medium enterprises succeeded in long-term mobile game operations through unique strengths, conservative development, social features, and RPG genres. Large enterprises succeeded in long-term operations through unique strengths, innovation, and non-RPG non-casual genres. Social features enabling player interaction showed negligible churn correlations in factor analysis and were commonly included across all condition combinations of long-term operational success patterns in QCA. These converging findings from multiple methods support network effects as a foundational retention mechanism. Counter-intuitively, long-term mobile game survival does not predict corporate profit growth. QCA suggests that long-term app survival is neither sufficient nor necessary for revenue growth. These findings offer practical implications for business leaders in freemium digital markets.