Search Results (215)

Companies in asset-intensive industries, such as aviation and railways, face unique digital transformation challenges due to the misalignment between the rapid evolution of digital technologies and decades-long asset lifecycles. Existing innovation frameworks are inadequate for managing this complexity, which in turn creates tensions between innovation requirements and operational reliability demands. This paper therefore investigates how asset-intensive companies can systematically integrate digital technologies, while fully complying with regulatory constraints and safety requirements. We employ a design science approach in a study of Nederlandse Spoorwegen (NS), the Dutch national railway operator, focusing specifically on the implementation of AI-driven CCTV systems within the operations of NS. Drawing on a literature review and participant-observer as well as interview data, we develop six design propositions that address the key digital transformation challenges of asset-intensive companies in the area of market readiness assessment, modular architecture, regulatory compliance, temporal coordination, ecosystem governance, and organizational capability development. Using these design propositions, we develop the Iterative Development & Adoption Model (IDAM) that operationalizes market maturity assessment through market readiness levels to guide make-or-buy transitions across four iterative phases: ideate, assess, realise, and review. This model includes a Development Reference Architecture for emerging technologies and an Integration Reference Architecture for more mature technologies, enabling concurrent sourcing strategies based on technological maturity. IDAM provides actionable guidance for decisions about technology adoption in asset-intensive contexts, thereby offering a systematic approach to innovation management in industries with very long asset lifecycles and huge regulatory constraints. Full article

Small and Medium-sized Enterprises (SMEs) face disproportionately high risks from Advanced Persistent Threats (APTs), which often evade traditional cybersecurity measures. Existing frameworks catalogue adversary tactics and defensive solutions but provide limited quantitative guidance for allocating limited resources under uncertainty, a challenge amplified by the growing use of AI in both offensive operations and digital forensics. This paper proposes a game-theoretic model for improving digital forensic readiness (DFR) in SMEs. The approach integrates the MITRE ATT&CK and D3FEND frameworks to map APT behaviors to defensive countermeasures and defines 32 custom DFR metrics, weighted using the Analytic Hierarchy Process (AHP), to derive utility functions for both attackers and defenders. The main analysis considers a non-zero-sum attacker–defender bimatrix game and yields a single Nash equilibrium in which the attacker concentrates on Impact-oriented tactics and the defender on Detect-focused controls. In a synthetic calibration across ten organizational profiles, the framework achieves a median readiness improvement of 18.0% (95% confidence interval: 16.3% to 19.7%) relative to pre-framework baselines, with targeted improvements in logging and forensic preservation typically reducing key attacker utility components by around 15–30%. A zero-sum variant of the game is also analyzed as a robustness check and exhibits consistent tactical themes, but all policy conclusions are drawn from the empirical non-zero-sum model. Despite relying on expert-driven AHP weights and synthetic profiles, the framework offers SMEs actionable, equilibrium-informed guidance for strengthening forensic preparedness against advanced cyber threats. Full article

This study examines the acceptance of artificial intelligence (AI) among professionals in accounting and auditing by applying the Technology Acceptance Model (TAM). The research addresses the broader question of how AI technologies are integrated into professional decision-making in financial services, with a focus on the determinants that shape user acceptance. A standardized survey, consisting of 21 items designed to measure TAM components, was distributed to accounting and auditing professionals. Data were analyzed through confirmatory factor analysis to validate the construct structure, and Pearson’s correlation and network analyses were used to identify relationships among variables. The results confirmed a robust seven-factor model with significant interrelations, highlighting AI knowledge as a central variable influencing perceived usefulness (PU), self-efficacy, and intention to use AI. These findings demonstrate that professional familiarity and confidence in AI tools are key drivers of technology acceptance. The study concludes that enhancing AI literacy can strengthen organizational readiness for digital transformation. Additionally, the research underscores the contribution of women-led scholarship in promoting responsible and inclusive approaches to AI adoption within the accounting and auditing sectors. Full article

In response to the growing need for environmental stewardship, Green Human Resource Management (GHRM) has emerged to incorporate sustainability in organizational practices, with Artificial Intelligence (AI) offering transformative potential. However, a comprehensive synthesis of the intersection between AI and GHRM is notably absent, prompting this review to systematically map the existing knowledge base and identify key trends. To bride this research gap, a systematic literature review was undertaken following the PRISMA framework, employing content and bibliometric analysis on 53 relevant articles published between 2018 and 2025. The analysis revealed five primary research themes, highlighting AI’s significant role in enhancing green recruitment, training, and performance management, while also underscoring critical challenges related to ethical considerations and organizational readiness. This review offers a structured synthesis of the AI-GHRM landscape, concluding with key interpretations that guide future research toward areas including adaptive systems, big data analytics, and the development of robust ethical frameworks, thereby serving as a valuable resource for advancing sustainable HRM practices. Moreover, this study directly contributes to the United Nations Sustainable Development Goals (SDGs), particularly SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation and Infrastructure), and SDG 12 (Responsible Consumption and Production), through emphasizing the strategic significance of AI-enabled Green HRM in fostering organizational sustainability. Full article

This study examines the adoption and implementation of the Zero Trust (ZT) cybersecurity paradigm using the Technology–Organization–Environment (TOE) framework. While ZT is gaining traction as a security model, many organizations struggle to align strategic intent with effective implementation. We adopted a sequential mixed-methods design combining 27 semi-structured interviews with cybersecurity professionals and a survey of 267 experts across industries. The qualitative phase used an inductive approach to identify organizational challenges, whereas the quantitative phase employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the hypothesized relationships. Results show that information security culture and investment significantly influence both strategic alignment and the technical implementation of ZT. Implementation acted as an intermediary mechanism through which these organizational factors affected governance and compliance outcomes. Strategic commitment alone was insufficient to drive effective implementation without strong cultural support. Qualitative insights underscored the importance of leadership engagement, cross-functional collaboration, and legacy infrastructure readiness in shaping outcomes. The findings emphasize the need for cultural alignment, targeted investments, and process maturity to ensure successful ZT adoption. Organizations can leverage these insights to prioritize resources, strengthen governance, and reduce implementation friction. This research is among the first to empirically investigate ZT implementation through the TOE lens. It contributes to cybersecurity management literature by integrating strategic, cultural, and operational dimensions of ZT adoption and offers practical guidance for decision-makers seeking to institutionalize Zero Trust principles. Full article

Digital Twins provide comprehensive capabilities to solve critical logistics problems such as visibility, monitoring, optimization, prediction, and simulation. This study explores the existing DT readiness assessment models in SCs and logistics, discovers their limitations, and proposes a conceptual model based on an organization’s internal and external attributes to strategize DT implementation in logistic functions. The results showed that the existing readiness assessment models have weaknesses and drawbacks, motivating the researchers to develop a new logistic DT readiness assessment model. This study identified six main organizational dimensions directly affecting measuring overall logistics’ DT readiness, which are management readiness, personnel readiness, information readiness, organization readiness, product readiness, and process flow readiness. Their relationship is mediated by Technology Integration and moderated by Supply Chain Complexity, which was tested using partial least squares structural equation modeling to show the importance of strategizing DT implementation in logistics. Full article

Purpose: The research explores the impact of change management practices—leadership support, employee involvement, and regulatory compliance —on the practice of sustainable healthcare in Saudi Arabia. Operational efficiency is treated not as a management practice but as a key outcome of effective change management. The research also examines patient readiness as a mediator influencing awareness, participation, and satisfaction. Design/methodology/approach: The study used a quantitative Saudi Arabian healthcare consumer survey. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze change management, patient readiness, and sustainable healthcare relations adoption. Findings: Findings indicate that change management plays a strong role in increasing patient adoption (β = 0.322; p = 0.083), but with large effects on awareness (β = 0.873; p < 0.001), engagement (β = 0.841; p < 0.001), and satisfaction (β = 0.881; p < 0.001), as adoption reflected through awareness, engagement, and satisfaction. Patient readiness as a mediator was significant with strong effects between change management and adoption (β = 0.571; p < 0.001). Originality/value: This research expands the Theory of Planned Behavior (TPB) by synthesizing it with strategic change management to predict patient readiness as a mediator of long-term adoption of healthcare in the Arab environment. Patient readiness is hypothecated as an observable behavioral construct to mediate organizational change practices—leadership, communication, and regulation—with individual adoption outcomes. The research provides theoretical and practical contributions for evidence-based healthcare policy and patient-led healthcare revolution. In addition, the study conforms with the United Nations Sustainable Development Goals (SDGs) including SDG 3 (Good Health and Well-being), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 12 (Responsible Consumption and Production), and shows how effective change management not only assists national healthcare reforms but also global sustainability goals. Full article

Background: Poland is one of six countries implementing the Finnish Smart Family practice under the Joint Action Health4EUKids, aimed at supporting families in adopting lifestyle counseling methods and preventing childhood obesity across the European Union. Material and method: Since March 2024, Poland has implemented Smart Family tools through training sessions for professionals who work or will work with families of children with excess body weight. A total of 295 individuals have been trained, including 52.2% dietitians, 34.9% nurses, and 12.9% school staff such as teachers, school counselors, and psychologists. Before and after the training sessions, participants completed a survey assessing their knowledge of the Smart Family Practice, and familiarity with supportive tools. Results: Among 295 participants, nearly half reported no prior experience with family-based lifestyle change interventions. Post-training, over 70% expressed readiness to implement the SMART FAMILY method, with high interest (80.7%), motivation (76.5%), and satisfaction (83.6%). Most recognized its potential to support healthy lifestyles and parental engagement (>85%). Key barriers included lack of family cooperation (87.8%), staff shortages (81.0%), limited training (78.4%), and insufficient resources (43%). Conclusions: A high level of acceptance and motivation among participants indicates that the SMART FAMILY method has the potential for effective adaptation in Poland. Its implementation requires strengthening specialists’ skills and providing appropriate organizational resources. Overcoming barriers such as lack of experience, limited time, and difficulties in engaging families is crucial to achieving lasting intervention outcomes. Full article

This research examines how artificial intelligence is reshaping business and labor structures through a sustainability lens. Drawing on survey data from 127 organizations and 14 case studies, we quantify workforce impacts while exposing methodological limitations in current projections. Our analysis reveals implementation variations of 37% across industries and 41% higher user adoption rates for hybrid governance approaches versus centralized models. The evidence supports a three-dimensional strategic framework for sustainable organizational development: comprehensive upskilling fostering behavioral change (2.7× higher implementation success), distributed innovation enabling cross-functional ideation (3.1× more identified use cases), and strategic integration aligning systems across departments (explaining 31% of implementation success variance). Organizations deploying all three dimensions achieved a 74% AI initiative success rate versus 12% for those using none. Implementation barriers include regulatory uncertainty, organizational resistance, and ethical considerations, with data infrastructure maturity (β = 0.32), executive sponsorship (β = 0.29), and change readiness (β = 0.26) explaining 58% of implementation success variance. Our findings indicate that sustainable adaptation capacity—not merely technological investment—determines which organizations successfully navigate this transformation while maintaining long-term organizational viability, workforce resilience, and contribution to broader sustainable development goals. Full article

In the context of accelerated digitalization, enterprises are increasingly adopting information-driven solutions to support managerial decision-making, with Enterprise Resource Planning (ERP) systems playing a crucial role in organizational development. Despite its importance, ERP adoption varies significantly across industries, particularly between developed and developing economies, where technological and structural differences persist. This paper proposes and validates a classification framework for assessing industry readiness for ERP adoption, based on an integrated PLS-SEM-MCDA methodological approach. PLS-SEM identified statistically significant factors and transformed them into weights to compare ERP user attitudes across eleven industries in Serbia and Slovenia. In addition, the TOPSIS-Sort method classified industries into high, moderate, and low readiness as predefined order classes. Finally, sensitivity analysis and comparative analysis are performed with AHP expert weights and the PROMETHEE-FlowSort method to determine the robustness of the PLS-SEM-TOPSIS-Sort results. The results show that the IT industry is the most consistent in adopting ERP systems. In contrast, other industries exhibit varying levels of readiness, depending on their degree of digital maturity and organizational preparedness. The proposed framework’s methodological flexibility allows it to be adapted to various contexts, making it suitable for future academic research and comparative studies. Additionally, the practical implications of the research are twofold. For ERP suppliers, the findings provide guidance on how to approach market segmentation and strategic positioning tailored to the specific needs of individual industries. For ERP users, their success in ERP adoption can be amplified by using the research insights as a benchmarking model. Full article

Background/Objectives: Open Notes—defined as patients’ electronic, portal-based access to clinicians’ narrative documentation within electronic health records (EHRs)—has become routine through policy and portal initiatives. In mental health (MH), transparency intersects with sensitive formulation and risk language, making outcomes contingent on documentation practices, release timing, and reader support. This scoping review mapped empirical evidence on experiences, perceived impacts, and implementation of Open Notes in MH across stakeholders and settings, deriving implications for practice, training, and policy. Methods: A PRISMA-ScR-guided review was conducted with a preregistered protocol on OSF. Eligible studies examined Open Notes in MH settings and reported stakeholder perspectives. Two reviewers independently screened and extracted data, analyzed through inductive narrative thematic synthesis. Results: Twenty-two studies (2012–2025) from the USA, Sweden, Germany, Canada, and international settings included surveys, qualitative interviews, mixed-methods designs, pilot and quasi-experimental implementations, and a Delphi consensus. Patients consistently reported improved comprehension, recall, empowerment, and—in some cases—greater trust. Large surveys identified error detection and patient-initiated corrections as safety mechanisms, while a minority reported worry or feeling judged by wording. Clinicians adapted documentation—modifying tone, wording, or candor—to minimize misinterpretation. Workload effects were generally modest, limited to occasional clarifications. Implementation and expert studies emphasize organizational readiness, training, patient preparation, and privacy-aware portal design as key enablers of safe transparency. Conclusions: In MH, Open Notes function as a communication and engagement tool that strengthens partnership, comprehension, and safety when implemented with attention to risk-sensitive documentation and privacy safeguards. Full article

The logistics sector contributes significantly to global warming, primarily through Scope 3 emissions. Green logistics practices (GLPs) can mitigate emissions and improve sustainability performance; however, their adoption remains limited due to high upfront costs and organizational barriers. This study aims to identify the driving factors of green logistics (GL) by conducting a systematic literature review following the PRISMA protocol. A total of 95 peer-reviewed articles published between 2016 and 2024 are analyzed. The review combines bibliometric and content analysis and develops a conceptual framework to guide future research. Findings reveal two main categories of drivers: (i) internal drivers, most notably top management commitment, which influences strategic direction, resource allocation, and organizational change; and (ii) external drivers, particularly institutional pressures. The study also identifies methodological patterns and theoretical gaps and proposes a theory–methodology–context agenda for future research. Practically, it shows how organizational readiness and supportive public policies can help overcome barriers, facilitate adoption, and promote more sustainable logistics systems. Full article

This study proposes and empirically assesses a bio-inspired conceptual framework, termed Digital DNA, for modeling Industry 5.0 transformation as a complementary extension of established Industry 4.0 principles with an explicit focus on human-centricity, sustainability, and resilience. Rather than positing a new industrial revolution, our positioning follows the European Commission’s view that Industry 5.0 complements Industry 4.0 by emphasizing stakeholder value and human-technology symbiosis. We encode organizational capabilities (genotype) into four gene groups, Adaptability, Technology, Governance, and Culture, and link them to five human-centric outcomes (phenotype). Twenty capability genes and ten outcome measures were scored, normalized (0–100 scale), and analyzed using correlations, K-means clustering, and mutation/drift tracking to capture both static maturity levels and dynamic change patterns. Results show that high Industry 5.0 readiness is consistently associated with elevated Governance and Culture scores. Three transformation archetypes were identified: Alpha, representing holistic socio-technical integration; Beta, with strong technical capacity but weaker cultural alignment; and Gamma, with fragmented capabilities and elevated vulnerability. The Digital DNA framework offers a replicable diagnostic tool for linking socio-technical capabilities to human-centric outcomes, enabling readiness assessment and guiding adaptive, ethical manufacturing strategies. Full article

The leisure industry exerts adverse effects on the natural environment, creating critical challenges for achieving clean and sustainable environmental goals. However, the potential role of metaverse technologies in mitigating these challenges remains underexplored. Therefore, this study explores how metaverse technologies can support clean and safe environmental objectives in Turkey and Lithuania. Specifically, the research aims to identify the socio-cultural, institutional, and technological barriers that arise during the integration of these technologies into sustainable environmental strategies. Using purposive sampling, semi-structured interviews were conducted with forty experts from both countries, including policymakers, academics, and industry professionals. The results indicate that variations in technological infrastructure, levels of digital readiness, socio-cultural acceptance, and institutional governance capacity significantly shape the feasibility of applying metaverse technologies in the leisure industry. Furthermore, the findings highlight that local needs, stakeholder expectations, and organizational resources play a crucial role in determining the effectiveness of these technologies in promoting a cleaner and more sustainable environment. The recommendations particularly emphasize enhancing technological infrastructure, expanding institutional collaborations, implementing legal reforms related to metaverse technologies, and addressing data security concerns. Overall, the study provides a comprehensive perspective that connects technology, recreation, and environmental science. Full article

This research develops and applies the IoTRIM model to assess the economic and operational implications of IoT integration in postal and courier enterprises in Slovakia. Combining a multi-criteria evaluation framework with an extended Cobb–Douglas production function, the analysis captures both readiness levels and their translation into output performance. The IoTRIM assessment reveals heterogeneous distributions of strengths across four strategic and technical pillars, with notable disparities between connectivity, data analytics, and interoperability capacities. Monte Carlo simulations under pessimistic, realistic, and optimistic scenarios highlight divergent digital trajectories among enterprises, with some demonstrating accelerated gains from IoT readiness while others face structural bottlenecks in infrastructure and process integration. Hypothesis testing indicates that while a positive and statistically significant relationship between IoT readiness and output is observed in selected cases, this effect is not universal across all enterprises and scenarios. However, the inclusion of IoT readiness consistently improves the explanatory power of the production function models. The findings underline that digital transformation outcomes depend not only on investment scale but also on systemic absorption capacity, including interoperability, data governance, and organizational alignment. The proposed approach offers both a methodological contribution for measuring digital readiness impacts and practical insights for strategic planning in the postal and courier sector. Full article