Artificial intelligence (AI) is developing rapidly and is gradually transforming traditional management control practices into intelligent management control, characterized by automation, analysis and decision-making. This research aims to explore this transition from traditional management control, focused on retrospective monitoring, to intelligent management control, by highlighting two further paradigms: predictive and ethical management control. The methodology is based on semi-structured interviews with Moroccan management controllers working in various sectors. These interviews provided in-depth insights into their experiences of using AI tools, the perceived benefits and the limitations encountered in their use. The results highlight that artificial intelligence makes several significant contributions to the work of management controllers, improving the efficiency of analyses, the quality of information and the speed of decision-making processes, thereby allowing them to focus on activities with higher added value. However, the study also highlights the need to develop new capabilities in prompt engineering, strategic communication and the management of human–machine relationships, in order to adapt to these transformations. Nevertheless, this evolution is facilitating a gradual repositioning of the management controller towards a more strategic role. Furthermore, it documents the specific characteristics of technology adoption in the African context, which is characterized by the phenomenon of shadow AI.
Despite the growing use of social media to promote green agricultural products, firms still face challenges in translating green advertising into purchase intentions. Drawing on dynamic capability theory and an ambidexterity perspective, this study examines two parallel consumer acceptance pathways involving user-generated content (UGC)-based social media green advertising and targeted green advertising on social media, with green trust as a mediating mechanism and sustainability-focused value orientation as a boundary condition. Survey data from 739 respondents were analyzed using partial least squares structural equation modeling. The results show that acceptance of both advertising approaches is positively associated with green trust and green purchase intention, with green trust partially mediating both relationships. Sustainability-focused value orientation strengthens the relationship between acceptance of UGC-based social media green advertising and green purchase intention but does not significantly moderate the relationship between acceptance of targeted green advertising on social media and green purchase intention. These findings extend the ambidexterity perspective to consumer-facing green advertising by showing how distinct advertising approaches operate through parallel acceptance pathways and converge on green trust as a shared psychological mechanism. The study also offers practical implications for designing more effective social media strategies to promote sustainable consumption.
Small and medium-sized enterprises (SMEs) play a pivotal role in advancing sustainability, yet many struggle to translate voluntary sustainability practices into structured, strategic business models. This study examines how this gap can be bridged between voluntary certification frameworks and emerging regulatory requirements, with a specific focus on workforce-related sustainability reporting under the European Sustainability Reporting Standards (ESRS). Using a qualitative case study of a Green Globe-certified, family-owned hotel, the research conducts a comparative gap analysis between existing organisational practices and corporate disclosure requirements, applying a Policy–Action–Target–Metric (PAT&M) framework. The findings reveal strong alignment in Policies and Actions (89%) but limited alignment in Targets and Metrics (14%), indicating a gap between sustainability activities and strategic performance management. The results highlight the need to transition from compliance-oriented initiatives to integrated, data-driven management systems. The findings also suggest that voluntary certification schemes, such as Green Globe, can be a useful first step in order to achieve better corporate reporting capabilities related to environmental, social and governance (ESG) issues. As practical implications, a roadmap solution is proposed to support system-level integration, transparency, and measurable outcomes for better business resilience.
Employee engagement remains one of the most widely studied constructs in organizational research. However, the ever-increasing involvement of Generation Z and Generation Y employees in the workplace raises the question of whether current employee engagement measuring tools are appropriate. The literature states that Generation Z employees are different than Generation X and the Baby Boomers. In this study, we developed and provided initial validation for a contemporary multidimensional measure of employee engagement using DeVellis and Thorpe’s nine-step scale development process. A sequential mixed-methods design integrated a comprehensive literature review, completed in 2024, phenomenological interviews with employees representing Generations X, Y, and Z, and psychometric evaluation of the resulting instrument. Contrary to expectations derived from portions of the generational literature, participants described a remarkably similar understanding of what employee engagement is across generations. However, the final factors show that the first factor of the six-factor instrument focuses on Person-Job Values/Passion/Purpose Fit, which is supported in the 2024–2025 literature; with factors two, three, and four aligning with the contemporary literature: Person-Colleague Fit, Person-Supervisor Fit, Person-Community Fit. The fifth factor focused on Person-Job Flexibility Fit, which is supported in the 2024–2025 literature. The sixth factor reflects Person-Organization Fit and aligns with the contemporary literature. Confirmatory factor analyses and validity testing provided initial evidence supporting the reliability and construct validity of the Multidimensional Employee Engagement Instrument (MEEI). The findings suggest that employee engagement is not simply an individual psychological state, but a multidimensional person–environment fit construct reflecting employees’ alignment with higher-order values: work, colleagues, supervisors, community, flexibility, and organizations. This study contributes a theoretically grounded and psychometrically supported instrument for advancing employee engagement research and practice.
Public–private partnerships (PPPs) are implemented through individual contracts, but their performance is often judged with indicators observed at broader sectoral or national levels. This study develops a measurement alignment framework comprising intervention–measurement alignment, statistical visibility, attribution distance, outcome completeness, and comparison credibility and applies it to Croatian PPPs. The analysis combines the national PPP register with Eurostat data for 2000–2024. It uses a six-sector difference-in-differences benchmark, applies small-cluster inference and a 9999-draw Webb wild-cluster bootstrap, adds hours worked and national-accounts gross fixed capital formation, and evaluates timing, pandemic, contamination, spillover, intensity, and leave-one-out sensitivity. In the six-sector benchmark sample, the current-price GVA coefficient is 0.149 and statistically uncertain, whereas the real GVA coefficient is 0.256 and remains supported by the wild-cluster bootstrap (p = 0.009). In the 16-sector comparison sample, current-price and real GVA estimates remain positive but are estimated with wider uncertainty. Employment, hours worked, real productivity, and real investment show no robust broad effects, while event-study diagnostics reveal poorer pre-treatment comparability in the 16-sector comparison sample. The evidence supports a cautious positive output association, not a general causal growth claim, and demonstrates that PPP accountability requires indicators aligned with project mechanisms, geography, timing, and accounting visibility. The framework explicitly recognizes environmental performance as a required outcome domain, but the available sector-level data do not permit a direct estimate of PPP environmental impacts.
Purpose: This study investigates the structural pathways driving the startup potential of Generation Z students in Romania’s post-transition economy. It examines the sequential relationship between Entrepreneurial Mindset (EM), Entrepreneurial Intentions (EIs), and Entrepreneurial Behavior (EB), focusing on the mediating role of intentions in bridging the gap between cognition and action. Design/methodology/approach: Using a quantitative explanatory design, data were collected through a two-stage hybrid framework from a sample of 215 Romanian business students associated with the Hackathon Innovation Labs (HILs), selected via a non-probability purposive sampling method. Hypotheses were tested using Structural Equation Modeling (SEM) with maximum likelihood estimation, supported by Confirmatory Factor Analysis (CFA) to ensure statistical rigor. Findings: Results confirm that EM is a robust predictor of EI, which significantly drives EB, explaining 45.2% of its variance. The findings highlight that intentions fully mediate the relationship, suggesting that a growth-oriented mindset turns into firm intentions to overcome institutional and cultural barriers. Originality: This research applies a rigorous SEM framework to a cohort of digital natives in an underrepresented Eastern European emerging market. It integrates mindset as a foundational cognitive precursor and provides empirical evidence of the sequential path to entrepreneurial behavior. Research limitations/implications: The study is limited by its sample size and geographic focus on Romanian business students. Future longitudinal research should explore external contingency factors, such as access to capital and ecosystem support, to validate model generalizability. Practical and social implications: Higher education should shift toward experiential programs like HILs, embedding credit-bearing hackathons and micro-credentials to foster an entrepreneurial mindset. Socially, sustaining this momentum with structured mentorship bridges the intention–action gap, transforming Gen Z’s digital potential into tangible economic value for the post-transition ecosystem.
This study examines how residents evaluate local government within Japan’s Liveable Well-Being City Indicator (LWCI) framework, with a focus on public service delivery and the application of machine learning (ML). Using a nationwide survey of 66,085 respondents, two dimensions of local government evaluation (Service Accessibility and Government Responsiveness) were examined using correlation analysis and Random Forest classification models. The findings indicate that differences between the two evaluation dimensions are better understood through patterns of relative predictive importance among shared factors than entirely distinct sets of variables. Service Accessibility was more strongly associated with functional and usability-related service factors, whereas Government Responsiveness was associated with a broader range of service-related and community-level conditions. The Random Forest models further identified differences in the relative importance of predictors across the two outcomes, reinforcing the distinction between their broader predictive patterns. These findings demonstrate that integrating ML with well-being assessments complements conventional statistical analysis by providing additional insight into the comparative predictive structure of policy-related factors.
AI-driven personalization has become a defining feature of digital advertising, yet whether it drives purchase intention directly or depends on other underlying mechanisms remains insufficiently understood, particularly in under-studied emerging markets. This study investigates how perceived relevance, usefulness, and privacy concerns shape perceived trust and purchase intention in response to AI-driven personalized advertising across Lebanon and Türkiye, two digitally distinct markets. Drawing on the Stimulus Organism Response model, Technology Acceptance Model, Privacy Calculus Theory, and Trust in Automation Theory, a quantitative cross-national design was employed, using a structured questionnaire administered to 802 social media users (394 Lebanon; 408 Türkiye), with data analyzed through partial least squares structural equation modeling and permutation-based multigroup analysis following partial measurement invariance. Results confirm perceived personalization has no direct effect on purchase intention, operating solely through relevance, usefulness, and privacy concerns; relevance and usefulness build trust while privacy concerns erode it, and trust, relevance, and usefulness each independently drive purchase intention. This study advances an asymmetric mediation account of AI advertising, positioning trust as the conduit through which privacy risk reaches behavior and, for managers, the lever converting personalization into purchase. Future research could examine these dynamics longitudinally or across other digitally emerging markets.
The integration of Artificial Intelligence (AI) into human resources management is driving a profound transformation in the evolution of management, and even more so in the management of human talent, which is the primary resource of any organization. This research provides an in-depth analysis of the impact of AI on core human resource management processes, covering the automation of operations that enables the exploration of dimensions such as talent acquisition, training, potential development, mental well-being, strategic workforce planning, job design, diversity, compensation, equity and inclusion, change management, culture and sustainability. The purpose of this study is to systematically synthesize the existing evidence on the impact of artificial intelligence on human management processes, identifying the scientific consensus, emerging contradictions, research gaps, and implications for sustainable organizational development. A systematic review was conducted of various sources published between 2020 and 2025 from databases such as ScienceDirect and Scopus, among others, using predefined Boolean search strategies, explicit inclusion and exclusion criteria and a structured thematic synthesis narrowing down the main studies based on search criteria. It was determined how algorithms are changing the employer-employee relationship within organizations. The findings indicate that the effectiveness of AI depends on the development of a hybrid intelligence that preserves the human factor consideration. It is concluded that AI enables the optimization of cultural change management, analytical precision, and ethical oversight—which are irreplaceable and critical human competencies in today’s digital age. This review contributes to the literature by providing a comprehensive synthesis of recent evidence, identifying unresolved research gaps, and proposing a future research agenda that will lead to the development of sustainable, responsible, and people-centered AI in human resource management.
Climate risk is increasingly reshaping firms’ operating environments, yet limited evidence exists on how climate-related pressures influence corporate green innovation and through which organizational mechanisms such effects occur. Drawing on induced technological change theory and dynamic capability theory, this study investigates how climate risk, reflected in firms’ exposure to extreme high-temperature days, affects green innovation among Chinese A-share listed manufacturing firms during 2010–2022. The results indicate that climate-related heat shocks significantly promote firms’ green innovation. Mechanism analyses show that this effect operates through two channels: increased R&D investment and enhanced adaptive capacity. Further analyses reveal that the innovation-promoting effect of climate-related pressures is strengthened by regional green finance development but weakened by firms’ financial slack. In addition, the positive effect is concentrated among non-state-owned enterprises and non-heavily polluting firms. This study contributes to the literature by extending induced technological change theory to the firm level and highlighting how climate-related pressures influence green innovation through both resource reallocation and organizational adaptation. The findings also provide new evidence on the roles of external financial support and internal resource conditions in shaping firms’ innovation responses to environmental change.
The digital transformation of shrimp aquaculture in Ecuador has accelerated the adoption of traceability technologies to improve transparency, regulatory compliance, and supply chain coordination. However, persistent structural limitations—such as technological fragmentation, low interoperability, and inconsistent data quality—continue to constrain their effectiveness. This study develops an approach to managing informational uncertainty in traceability systems, grounded in information theory and operationalized through the Technological Management Model for Shrimp Production (TMMT-SP). Methodologically, the research follows an abductive systemic modeling approach, integrating a systematic literature review, structural analysis of the production system, and ontological modeling to identify and classify interdomain gaps. The findings show that informational uncertainty emerges as a structural property of the system, resulting from misalignments across informational, technological, and governance dimensions. These misalignments limit the coherence, reliability, and integration of traceability processes. In response, the study proposes a structural entropy-based framework (understood as an operational representation of systemic informational dispersion) to diagnose, prioritize, and address these gaps, shifting the focus from isolated technological adoption toward systemic coherence. This approach provides a conceptual and methodological basis for designing technology management strategies to reduce uncertainty in complex production systems.
This study proposes a conceptual model of smart innovation to examine internationalization processes in traditional, territorially embedded industries, with a focal empirical focus on Sogrape, Portugal’s leading wine company, situated within the Vinho Verde wine sector. While digital transformation is increasingly recognized as a driver of competitiveness, its role in shaping internationalization strategies within regional agri-food systems remains insufficiently theorized. To address this gap, the study adopts a modified Delphi-based qualitative approach involving a panel of experts composed mainly of Sogrape managers and complemented by independent producers from the Vinho Verde wine sector. Through two iterative rounds of structured expert inquiry, the research identifies key mechanisms linking digital transformation, organizational capabilities, territorial identity, and international market expansion. The findings are synthesized into an integrative conceptual model that articulates how smart innovation, understood as the strategic alignment of digital capabilities, organizational processes, and territorial assets, may support internationalization processes in territorially embedded settings. The model emphasizes the role of digital platforms, data-driven decision-making, and narrative-driven place positioning in translating territorial identity into competitive value in global markets. Importantly, the study does not claim to provide representative evidence of the Vinho Verde wine sector as a whole. Rather, it develops a focal-case-based analytical architecture, grounded primarily in Sogrape’s organizational context and qualified by complementary insights from independent producers. The study contributes to the literature by bridging digital transformation, internationalization, and territorial value creation within a unified conceptual framework. From a managerial perspective, it offers analytically grounded insights that may inform strategic reflection in wine firms and other territorially embedded agri-food sectors, subject to contextual adaptation and further empirical validation.
Intellectual capital disclosure (ICD) is believed to enhance transparency and reduce information asymmetry, yet its voluntary nature raises questions about its effectiveness, particularly in emerging markets. This study investigates whether ICD mediates the relationship between corporate governance and firm performance in Jordan, an emerging market that mandated corporate governance reports in 2017. Using panel data from 391 firm-year observations (2021–2023) of firms listed on the Amman Stock Exchange, we employ pooled OLS regression with robust standard errors. Only three of eighteen hypotheses are supported. Board size significantly influences relational (RCD) and structural capital disclosures (SCD). Audit committee meetings influence RCD. However, no ICD component affects firm performance, and no mediation effects exist. The results indicate that ICD does not mediate the corporate governance-firm performance relationship. The findings question the effectiveness of voluntary ICD; this type of voluntary disclosure may be insufficient to achieve transparency goals in emerging markets. We argue that mandatory, standardized ICD requirements may be necessary to enhance comparability, reduce information asymmetry, and improve governance effectiveness. Regulators should consider piloting mandatory ICD reporting for large listed firms.
This study examines students’ job search behaviour in the context of an increasingly digital labour market, focusing on preferred employer contact channels and the use of professional networking platforms. Despite the growing importance of digital tools for recruitment and employability, it remains unclear how students actually engage with these channels. The study is based on quantitative data collected through a structured questionnaire administered in person to 209 university students in Slovakia. The analysis employs descriptive statistics, chi-square tests and binary logistic regression to examine differences in preferences and the determinants of platform use. The findings show that job portals remain the dominant employer contact channel, while social media platforms, including LinkedIn, are significantly less utilised. A key result is the identification of a gap between LinkedIn awareness, profile ownership, and its actual use for job search. The results further indicate that job portal preference differs by field of study, while employment status is not significantly associated with the analysed employer contact channels. The study contributes to the literature by highlighting the importance of behavioural engagement in digital job search and offers implications for universities, students, and employers.
Human-like virtual influencers (VIs) have become an increasingly important component of social media marketing. Their human-like appearance can simultaneously attract users and, meanwhile, evoke discomfort associated with the uncanny valley. This study utilized quantitative research via partial least squares structural equation modeling. A total of 845 Instagram users contributed to the dataset. The findings demonstrated that informative content did not significantly influence Instagram users’ engagement intentions, whereas entertaining content exerted a favorable influence. Simultaneously perceived innovativeness was the strongest antecedent, while perceived personalization was also significant. In addition, both cognitive and affective empathy significantly strengthen parasocial relationships, which subsequently increase users’ engagement intentions toward human-like VIs. This study contributes in three ways. First, it identifies the relative importance of content, social relationships, and personal gratifications in explaining engagement intentions with human-like VIs. Second, it extends research by distinguishing the complementary roles of cognitive and affective empathy in fostering parasocial relationships with human-like VIs. Third, the findings suggest that cognitive and affective empathy may help explain why users form meaningful social relationships with highly human-like VIs despite concerns associated with perceived artificiality, thereby offering a more nuanced understanding of engagement intentions in the context of virtual influencer marketing.
Artificial intelligence (AI) is increasingly transforming banking, yet responsible adoption depends not only on technical deployment but also on organizational readiness, governance capacity, monitoring practices, and the capacity to scale AI responsibly. This study examines AI adoption, governance readiness, maturity, perceived benefits, adoption barriers, and scaling intention in the Albanian banking system. Based on a cross-sectional survey of 85 professionals from 15 institutions, including all 12 banks operating in Albania and 3 additional financial institutions, the study applies the Technology–Organization–Environment framework together with principles of responsible AI governance. The analysis uses reliability and validity diagnostics, common-method diagnostics, robust OLS regressions, institution-clustered inference, bootstrap confidence intervals, PLS-SEM robustness analysis, and sensitivity checks. The findings show that AI adoption is visible but uneven: more than half of respondents reported active or pilot AI use, while integration, monitoring, and benefit measurement remain less developed. Data and Technology Readiness and Environmental/Regulatory Pressure were positively associated with Capability-Governance Readiness, which was positively associated with Perceived Benefits. Perceived Benefits were positively associated with Intention to Invest in or Scale AI, whereas Adoption Barriers showed no statistically significant association with scaling intention. The study provides exploratory evidence from a small banking system, indicating that responsible AI development requires the alignment of technological foundations, organizational capability, governance structures, monitoring routines, responsible-use orientation, and benefit-measurement practices.
This study examines how Female-Associated Leadership Practices (FALPs) are associated with firm performance in Ecuadorian small and medium-sized enterprises (SMEs) through organizational governance and strategic orientation. Drawing on Upper Echelons Theory, social role theory, expectation states theory, and gender and leadership research, FALPs are conceptualized as perceived leadership practices frequently linked to participative decision-making, collaboration, ethical consideration, innovation stimulation, and long-term orientation. This conceptualization avoids treating leader gender, gender diversity, women’s representation in management, and leadership style as interchangeable constructs. Using a quantitative cross-sectional design, firm-level data from 300 SMEs were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that FALPs are not directly associated with firm performance. Instead, they are positively associated with governance quality and strategic orientation, both of which are, in turn, positively associated with firm performance. Strategic orientation represents the strongest indirect pathway, while governance is associated with performance both directly and indirectly through strategic orientation. These findings provide a process-based explanation for inconsistent evidence on gender-related leadership practices and firm outcomes. Practically, the study suggests that participative, ethical, collaborative, innovation-oriented, and long-term leadership practices may support SMEs by strengthening governance quality and strategic capabilities.
Despite longstanding conceptual and measurement concerns surrounding transformational leadership, environmental applications of the paradigm have continued to proliferate through target-specific formulations and increasingly complex explanatory models. Yet whether these developments have resolved, or merely reproduced, the broader theoretical and methodological concerns that characterize transformational leadership research remains unclear. Against this backdrop, this systematic review, conducted and reported in accordance with the PRISMA 2020 guidelines, critically synthesizes the empirical literature on transformational leadership in employee green behavior research while situating it within this broader theoretical and methodological context. Peer-reviewed English-language articles published since 2000 were retrieved from Scopus, Web of Science, and ABI/INFORM and screened against predefined eligibility criteria, resulting in 64 studies. Results revealed limited empirical engagement with the theory’s linchpin of follower transformation. Rather than modeling change in follower self-concept, most studies adopted Bass’s four-pillar framework and examined associations between follower-perceived behaviors of transformational leaders and environmental outcomes within diverse mediational and conditional process models. Across almost all studies, higher perceptions of transformational leadership were positively associated with employee green behavior, irrespective of whether the construct was operationalized using general or environmentally specific formulations. Organizational factors, most notably perceived green organizational climate, emerged as the most frequently examined mediating mechanism and contextual boundary condition linking transformational leadership to employee green behavior. Both general and target-specific formulations were predominantly operationalized using measures based on the Multifactor Leadership Questionnaire (MLQ), raising concerns regarding the intelligibility of cumulative evidence. We conclude by outlining a research agenda aimed at enhancing theoretical coherence, measurement validity, and methodological rigor.
The dynamic capabilities perspective explains how firms sustain a competitive advantage in contemporary rapidly changing environments, yet it still lacks empirical accounts of how the three high-level capabilities of sensing, seizing, and transforming become observable processes through managerial practices. The study examines Thunder Tiger, a firm that developed into a leading global brand in the technologically dynamic and highly competitive radio-control model industry, and uses 30 strategic initiatives identified from its 36-year development trajectory as the units of analysis. Adopting the extended case method, we conduct simultaneous coding across two dimensions: the core content of high-level capabilities and observable managerial practices. We develop an analytical framework for dynamic capability processes comprising three layers: the three high-level capabilities, four functional domains, and twelve process items. Through this framework, we show how high-level capabilities can be linked to observable managerial practices in Thunder Tiger’s strategic initiatives.
Gender Equality Plans (GEPs) have been an eligibility requirement for Horizon Europe funding since 2022, yet formal adoption does not necessarily alter organizational routines, culture, or resource allocation. This article examines the process of moving from compliance toward institutionalized practice through a longitudinal single-case study of the University of Primorska (UP), a smaller university in a resource-constrained Widening-country context. We compare the first analytical observation period (2021–2025), based on its 2021–2027 GEP, with GEP 2.0 (2026–2030). Evidence combines documentary analysis, selected gender-disaggregated indicators, three focus groups (n = 24), and aggregated staff-survey results for 2024–2025. We develop the Gender Equality Plan Maturity Index (GEP-MI), an unweighted six-dimensional heuristic scored from 0 to 18. The document-based, triangulated score rises from 7 to 15, indicating more explicit governance, data routines, and resourcing, but not durable implementation outcomes. Qualitative evidence illustrates three overlapping categories associated with the paper–practice gap: passive resistance (skepticism and box-ticking), active ideological resistance (naturalization and denial), and structural implementation constraints (including administrative infeasibility and unequal care burdens). A documentary comparison with the Universities of Ljubljana and Maribor contextualizes differences in formal design; it does not establish the prevalence of these categories beyond UP. We define audit-induced decoupling under constrained resources as the risk that audited requirements redirect scarce capacity toward demonstrable compliance rather than substantive change. The case offers a transparent monitoring heuristic and suggests that proportionate capacity support warrants consideration alongside European conditionality.
