Search Results (3,116)

Fileless malware is a type of malware that does not rely on executable files to persist or propagate. Unlike traditional file-based malware, fileless malware is more difficult to detect and remove, posing a significant threat to organizations. This paper introduces a novel hybrid analysis model that combines static and dynamic analysis techniques to identify fileless malware. Applied to four real-world and two custom-created fileless malware samples, the proposed model demonstrated its qualitative effectiveness in uncovering complex behaviors and evasion tactics, such as obfuscated macros, process injection, registry persistence, and covert network communications, which often bypass single-method analyses. While the analysis reveals the potential for significant damage to organizational reputation, resources, and operations, the paper also outlines a set of mitigation measures that cybersecurity professionals and researchers can adopt to protect users and organizations against threats posed by fileless malware. Overall, this research offers valuable insights and a novel analysis model to better address and understand fileless malware threats. Full article

Employee turnover remains a critical challenge for organizations, prompting an examination of how leadership approaches influence employees’ intentions to leave. This study investigates the impact of transformational leadership on turnover intention, focusing on emotional exhaustion and creativity as potential mediators. The study employs a quantitative design grounded in leadership and organizational psychology theory and surveys 182 professionals working in the information technology sector across Bosnia and Herzegovina, Croatia, Serbia, and Montenegro. Structural equation modeling reveals that transformational leadership reduces turnover intention by alleviating emotional exhaustion, highlighting the importance of psychological well-being in employee retention. While transformational leadership enhances employee creativity, creativity did not significantly mediate turnover intention in this context. These findings suggest that strategies that foster engagement and reduce burnout in knowledge-intensive industries can strengthen organizational commitment and improve retention. This study contributes to the understanding of behavioral mechanisms linking leadership to employee outcomes and offers actionable insights for modern organizations aiming to address turnover through supportive, empowering leadership practices. Additional mediators and contextual variables should be explored in further research. Full article

Current learning and development approaches often struggle to capture dynamic individual capabilities, particularly the skills they acquire informally every day on the job. This dynamic creates a significant gap between what traditional models think people know and their actual performance, leading to an incomplete and often outdated understanding of how ready the workforce truly is, which can hinder organizational adaptability in rapidly evolving environments. This paper proposes a novel dynamic learner-state ecosystem—an AI-driven solution designed to bridge this gap. Our approach leverages specialized AI agents, orchestrated via the Model Context Protocol (MCP), to continuously track and evolve an individual’s multi-dimensional state (e.g., mastery, confidence, context, and decay). The seamless integration of in-workflow performance data will transform daily work activities into granular and actionable data points through AI-powered dynamic xAPI generation into Learning Record Stores (LRSs). This system enables continuous, authentic performance-based assessment, precise skill gap identification, and highly personalized interventions. The significance of this ecosystem lies in its ability to provide a real-time understanding of everyone’s capabilities, enabling more accurate workforce planning for the future and cultivating a workforce that is continuously learning and adapting. It ultimately helps to transform learning from a disconnected, occasional event into an integrated and responsive part of everyday work. Full article

As artificial intelligence (AI) becomes increasingly embedded in organizational development, understanding how leadership shapes employee responses to AI is critical for fostering workplace innovation. Drawing on trait activation theory, this study develops a theoretical model in which employee AI trust enhances innovative performance through AI crafting. Paternalistic leadership serves as a situational moderator, while the leader’s AI opportunity perception functions as a higher-order moderator. A three-wave survey was conducted with 523 employees from 14 AI-intensive manufacturing firms in China. Results show that the interaction between AI trust and paternalistic leadership positively predicts both AI crafting and innovative performance. In addition, AI crafting mediates the effect of the interaction term on innovative performance. Furthermore, the leader’s AI opportunity perception moderates this interactive effect: when this perception is high, the positive impact of AI trust and paternalistic leadership on AI crafting is significantly stronger; when it is low, the effect weakens. These findings contribute to the literature by clarifying the situational and cognitive conditions under which AI trust promotes innovation, thereby extending trait activation theory to AI-enabled workplaces and offering actionable insights for leadership development in the intelligent era. Full article

This study examines the moral agency of French secondary school headteachers through the lens of the theory of conventions. Using qualitative data from interviews with fifteen headteachers involved in professional development, this study explores how these leaders justify their practices within a centralized, bureaucratic, and hierarchical education system. It identifies a variety of conventions—civic, domestic, industrial, project, market, inspired, and fame—that headteachers draw on to navigate institutional constraints, manage professional relationships, and foster pedagogical and organizational change. Particular attention is given to how civic and domestic conventions shape leadership discourse and practices, especially regarding trust building, decision making, and reform implementation. We also compare the French context with international examples from the International Successful School Principalship Project (ISSPP), focusing on Nordic countries, where leadership emphasizes democratic participation, professional trust, and shared responsibility. This study underscores the uniqueness of the French leadership model, which resists managerial and market logics while remaining rooted in republican and egalitarian ideals. It concludes by advocating for a more context-aware, ethically grounded, and dialogical approach to school leadership. Full article

This theoretical essay aims to analyze some of the socio-economic innovations introduced by Platform Capitalism Specifically, it focuses on two main aspects: first, the digital platform as a radical organizational innovation. Digital platforms represent a structural novelty in the market economy, signaling a new organization of production and labor. Second, the essay examines the role of platforms in directly generating value through the concept of “network value”. To this end, it explores the function of “business intelligence” as a strategic and competitive tool. Finally, the paper discusses the key issues associated with platform capitalism, which could threaten its social sustainability and contribute to economic and financial instability. These issues include the increasing commodification of everyday activities, the devaluation of paid labor in favor of free production driven by platform users (the so-called prosumers), and the emergence of proprietary and financial monopolies. Hence, digital platforms do not inherently ensure comprehensive social and environmental sustainability unless supported by targeted economic policy interventions. Conclusively, it is emphasized that defining robust social welfare frameworks—which account for emerging value creation processes—is imperative. Simultaneously, policymakers must incentivize the proliferation of cooperative platforms capable of fostering experimental circular economy models aligned with ecological sustainability. Full article

Flexible work arrangements have the potential to enhance work–life balance and contribute to more sustainable work environments. However, they may also increase fatigue and lead to greater work–life conflict (WLC). This study offers a novel contribution by examining the relationship between flexible work arrangements—focusing in particular on the cognitive demands of flexible work (CDFW), which encompass the task structuring, scheduling of working times, planning of working place, and coordination with others—and WLC. Specifically, the study investigates the mediating role of workload in this relationship. Furthermore, it also explores whether perceived organizational support (POS) moderates the indirect relationships between CDFW and WLC, within the framework of the Job Demands-Resources (JD-R) model. Data were collected from a sample of 419 employees in the Italian public sector. The study also controls for potential confounding variables, such as age, gender, duration of employment in public administration, and weekly working hours, to account for their influence on work–life balance and workload. The results highlight a significant positive relationship between planning of the working place and WLC. Additionally, workload plays a mediating role between CDFW subdimensions and WLC. However, POS does not moderate the mediated relationship between CDFW and WLC. Full article

Sustainability has emerged as a critical issue in development. Digital transformation functions as both an enabler and an effective tool for promoting sustainability. Strategy plays a pivotal role in the process of digital transformation. However, there is a paucity of existing research focused on strategic renewal in digital transformation within the context of China. This study employs organizational learning theory to examine the antecedents and consequences of strategic renewal in digital transformation. Data were collected from 389 government employees through a questionnaire survey and a quantitative analysis was performed to evaluate four hypotheses using structural equation modeling (SEM). The results indicate that knowledge acquisition and organizational memory significantly influence strategic renewal, which in turn affects government performance. The findings of this study could serve as a guide and provide concrete practical approaches for successful digital transformation among governments, thereby laying a foundation for sustainable development. Full article

As an example of pedagogical approaches that blend online and face-to-face instruction, the flipped classroom model has seen exponential growth in business schools. To explore its effectiveness, expectancy-value theory and cognitive load theory were employed to develop a framework linking students’ perceived usefulness of the online and in-person content to their pre-class preparation, class participation, perceived learning, and skills development. A preliminary test of this framework was conducted using a flipped Organizational Behavior course within a business diploma program at a publicly funded Canadian college. The perceived usefulness of the online component was positively associated with students’ pre-class preparation, which, in turn, was positively related to both their perceived learning and skills development. Implications for practice and directions for future research are discussed. Full article

The construction of stochastic models and the use of stochastic simulations for their analysis constitute research methods used in the analysis of stochastic processes. These methods can be applied to processes carried out in underground mines. For mining processes, carried out, e.g., in hard coal mines, it is noticed that the influence of factors generally referred to as geological–mining and technical–organizational may cause a given process to be treated as not fully defined (not necessarily in terms of the process technology, but, e.g., taking into account the time taken for its implementation). This article draws attention to the possibilities of reducing the stochastic model based on the use of the properties of the convolution of probability density functions. Functions that were considered appropriate for describing the processes discussed based on time-based studies were presented. The mechanism of operation of the proposed model reduction was discussed. Reduction carried out in this way eliminates the need to analyze these parts of the model, e.g., using the stochastic simulation method. This reduction leads to simplification of the model and the calculations, which translates into the effectiveness of the research. Full article

Background: Digital transformation is increasingly present in modern logistics, especially in the context of sustainability and circularity pressures. The integration of technologies such as Internet of Things (IoT), Radio Frequency Identification (RFID), and automated platforms involves not only infrastructure but also a strategic vision, a flexible organizational culture, and the ability to support decisions through artificial intelligence (AI)-based systems. Methods: This study proposes an extended conceptual model using structural equation modelling (SEM) to explore the relationships between five constructs: technological change, strategic and organizational readiness, transformation environment, AI-enabled decision configuration, and operational redesign. The model was validated based on a sample of 217 active logistics specialists, coming from sectors such as road transport, retail, 3PL logistics services, and manufacturing. The participants are involved in the digitization of processes, especially in activities related to operational decisions and sustainability. Results: The findings reveal that the analysis confirms statistically significant relationships between organizational readiness, transformation environment, AI-based decision processes, and operational redesign. Conclusions: The study highlights the importance of an integrated approach in which technology, organizational culture, and advanced decision support collectively contribute to the transition to digital and circular logistics chains. Full article

Shift organizations in automotive manufacturing often rely on manual task allocation, resulting in inefficiencies, human error, and increased workload for supervisors. This research introduces an automated solution using the Kuhn-Munkres algorithm, integrated with the Moodle learning management system, to optimize task assignments based on operator qualifications and task complexity. Simulations conducted with real industrial data demonstrate that the proposed method meets operational requirements, both logically and mathematically. The system improves the start of shifts by assigning simpler tasks initially, enhancing operator confidence and reducing the need for assistance. It also ensures that task assignments align with required training levels, improving quality and process reliability. For industrial practitioners, the approach provides a practical tool to reduce planning time, human error, and supervisory burden, while increasing shift productivity. From an academic perspective, the study contributes to applied operations research and workforce optimization, offering a replicable model grounded in real-world applications. The integration of algorithmic task allocation with training systems enables a more accurate matching of workforce capabilities to production demands. This study aims to support data-driven decision-making in shift management, with the potential to enhance operational efficiency and encourage timely start of work, thereby possibly contributing to smoother production flow and improved organizational performance. Full article

As artificial intelligence (AI) technology becomes increasingly widespread in organizations, its impact on individual employees’ psychology and behavior has garnered growing attention. Existing research primarily focuses on AI’s effects on organizational performance and job design, with limited exploration of its mechanisms influencing individual employees, particularly in the critical area of risk-taking behavior, which is essential to organizational innovation. This research develops a moderated mediation model grounded in social cognitive theory (SCT) to explore how AI usage affects the willingness to take risks. A three-wave longitudinal study collected and statistically analyzed data from 442 participants. The findings reveal that (1) AI usage significantly enhances employees’ willingness to take risks; (2) self-efficacy serves as a partial mediator in the connection between AI usage and the willingness to take risks; and (3) learning goal orientation moderates both the relationship between AI usage and self-efficacy, as well as the mediating effect. This research enhances our understanding of AI’s impact on organizational behavior and provides valuable insights for human resource management in the AI era. Full article

In crisis-stricken economies, leadership effectiveness increasingly hinges not on technical expertise alone but on emotional competence. While emotional intelligence (EI) has been widely acknowledged as a catalyst for effective leadership and employee outcomes, its role in volatile and resource-scarce contexts remains underexplored. This study addresses this critical gap by investigating the impact of five core EI dimensions, namely self-awareness, self-regulation, motivation, empathy, and social skills, on employee performance amid Lebanon’s ongoing multidimensional crisis. Drawing on Goleman’s EI framework and the Job Demands–Resources theory, the research employs a quantitative, cross-sectional design with data collected from 398 employees across sectors in Lebanon. Structural Equation Modeling revealed that all EI dimensions significantly and positively influenced employee performance, with self-regulation (β = 0.485) and empathy (β = 0.361) emerging as the most potent predictors. These findings underscore the value of emotionally intelligent leadership in fostering productivity, resilience, and team cohesion during organizational instability. This study contributes to the literature by contextualizing EI in an under-researched, crisis-affected setting, offering nuanced insights into which emotional competencies are most impactful during prolonged uncertainty. Practically, it positions EI as a strategic leadership asset for crisis management and sustainable human resource development in fragile economies. The results inform leadership training, policy design, and organizational strategies that aim to enhance employee performance through emotionally intelligent practices. Full article

This study explores how corporate governance reforms can enhance financial reporting quality and organizational transparency, focusing on Greece’s transition from Law 3016/2002 to Law 4706/2020. The legislative reform aimed to modernize governance structures, align national practices with international standards, and strengthen investor protection in a post-crisis economic environment. Moving beyond a simple legal comparison, the study examines how Law 3016/2002’s formal compliance model contrasts with Law 4706/2020’s more substantive accountability framework. We hypothesize that Law 4706/2020 introduces substantively stronger governance mechanisms than its predecessor, thereby improving transparency and investor protection, while compliance with the new law imposes materially greater administrative and financial burdens, especially on small- and mid-cap firms. Methodologically, the research employs a narrative literature review and a structured comparative legal analysis to assess the administrative and financial implications of the new law for publicly listed companies, focusing on board composition and diversity, internal controls, suitability policies, and disclosure requirements. Drawing on prior comparative evidence, we posit that Law 4706/2020 will foster governance and disclosure improvements, enhanced oversight, and clearer board roles. However, these measures also impose compliance burdens. Due to the heterogeneity of listed companies and the lack of firm-level data following Law 4706/2020’s implementation, the findings are neither fully generalizable nor quantifiable; future quantitative research using event studies or panel data is required to validate the hypotheses. We conclude that Greece’s new framework is a critical step toward sustainable corporate governance and more transparent financial reporting, offering regulators, practitioners, and scholars examining legal reform’s impact on governance effectiveness and financial reporting integrity. Full article