Journals Published by Vilnius Tech
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Integration of Lean Six Sigma into earned value management using system dynamics
No full textA Few Lean Six Sigma (LSS) papers were studied during the construction project’s progress. This study proposes the integration of LSS, system dynamics (SD), and earned value management (EVM) as a comprehensive toolkit for datadriven decision-making. Significant waste- and quality-related interdependencies were identified using DEMATEL techniques with 27 Saudi construction experts. SD with two interdependent models of waste causes (WCs) and quality causes (QCs) were utilized to assess the project’s performance. Two metrics were employed: the sigma rating and the value-added ratio in the EVM generated by the developed SD model. The findings indicated that eliminating WCs had little impact on enhancing the project performance in the early stages of the project. The impact increased with the progress of the project. The improvement of the project quality was minimal for “increases of errors and omissions in design documents” and maximum for “increasing morale and attitude affect the quality of the project”
Geopolitical risks, market volatility, and tech firms involved in quantum computing
No full textThis study examines how global uncertainty influences the financial dynamics of technology firms involved in quantum computing, a strategically significant but structurally fragile segment of emerging deep-tech markets. Using daily data from January 2015 to May 2025, the analysis integrates principal component decomposition, panel regression, Granger causality testing and volatility diagnostics to assess the transmission of market volatility and geopolitical risk. The findings show that market volatility, proxied by the VIX index, exerts a persistent and adverse influence on stock returns, confirming its role as a systemic risk factor. Geopolitical risk, measured through the ACT and THREAT sub-indices of the Geopolitical Risk Index (GPR), also affects return behaviour, but through asymmetric and time-varying transmission mechanisms that emerge under heightened uncertainty and global strategic tension. The results further reveal heterogeneous vulnerability profiles across firms, indicating conditional risk spillovers rather than uniform market reactions. The study contributes new empirical evidence on the interplay between financial and geopolitical risk in advanced technology sectors and offers a replicable framework for uncertainty modelling in frontier markets
An integrated vision-based dynamic collision risk assessment framework of workers and mobile machinery on construction site
No full textThe concepts of environmental impact index and spatial conflict degree have gained prominence in enhancing the controllability of collision accidents and mitigating the likelihood of collisions during construction processes. Nevertheless, prior studies predominantly focused on exploring collisions in terms of proximity and congestion between pairs of entities, thereby overlooking a comprehensive consideration of workers, construction machinery, environmental factors, and the spatial interaction of specific activities.To this end, this study aims to propose an integrated vision-based dynamic collision risk assessment framework by setting workers and mobile machinery as targeted research objectives and embedding a comprehensive risk assessment model in the proposed framework, thereby comprehensively assessing four types of risk factors (i.e., proximity, congestion, environmental impact index, and spatial conflict), and visualize the hierarchy of risk warnings. Firstly, a comprehensive risk assessment model was developed by using the fuzzy comprehensive evaluation method. This is followed by developing a dynamic risk assessment framework to extract the spatial information of the monitored objects by using computer vision as the underlying data of the risk factors. Finally, the proposed integrated framework was validated by an experimental study. This experiment’s safety risk assessment results are consistent with expectations, which largely illustrates the effectiveness of the evaluation model constructed in this paper. For the vision module, the accuracy of classification and monitoring is more than 95%, and the speed of the object detection algorithm to process the video is about 10 frames per second, which shows the feasibility of this study
Substitution or creation? Identifying the role of artificial intelligence in employment
Full text linkRecognising the significant role of artificial intelligence in the labour market is essential for China to develop sustainably. The research utilises the mixed frequency vector auto-regression (MF-VAR) technique, which would innovatively incorporate data at different frequencies into one model to identify the intricate correlation between the monthly artificial intelligence index (AII) and the quarterly unemployment rate (UR) in China. Through comparison, the MF-VAR method has a more substantial explanatory power than the low-frequency VAR (LF-VAR) model, the impulse responses of the former reveal that AII exerts favourable and adverse influences on UR. Among them, the positive effect occurs on the AII in the first and second months. In contrast, the negative one appears on the AII in the third month, highlighting that artificial intelligence has both stimulating and inhibiting effects on the labour market in China. By analysing UR’s predictive error variance decomposition, the total impact of China’s artificial intelligence technology on employment is a substitution; this outcome is accordant with the theoretical dis¬cussion. In the new round of scientific and technological revolution and industrial transformation, meaningful recommendations for China would be put forward to avert the wave of unemployment brought by the development of artificial intelligence technology.
First published online 09 September 202
A uniformly accurate hybrid difference approximation of a system of singularly perturbed reaction-diffusion equations with delay using grid equidistribution
Full text linkThis paper presents a uniformly accurate difference approximation for a system of singularly perturbed reaction-diffusion equations with delay. The proposed method utilizes an appropriate combination of exponential and cubic spline difference schemes. It employs grid equidistribution to address the challenges posed by the multiscale nature of these systems, which often feature sharp gradients and boundary layers. The grid is generated based on the equidistribution of a positive monitor function, a linear combination of a constant floor and a power of the second derivative of the solution. By using adaptive mesh generation and a spline difference method, the approach enhances the accuracy of the numerical solutions while maintaining computational efficiency. Numerical experiments validate the uniform convergence and theoretical findings, demonstrating the method’s robustness irrespective of the perturbation parameter size
Enhancing creative professional competence in foreign language acquisition for future environmental designers in Ukraine: a systematic review
Full text linkThis comprehensive study investigates the development of creative professional competence in foreign language among students enrolled in Ukraine’s Environmental Design educational programmes. Drawing on survey data from 226 participants, the research highlights the growing recognition of the role of English language proficiency in equipping future environmental designers for global, interdisciplinary practice. The findings reveal that while a majority of students appreciate the importance of such competence, significant gaps remain in curriculum structure, resource accessibility, and instructional design. In particular, students report insufficient instructional hours and a lack of integration of authentic, profession-specific English materials – challenges that hinder the acquisition of specialized communicative skills. The study emphasizes that foreign language education must go beyond basic instruction and instead be embedded within real-world, design-related contexts. It advocates for the adoption of content and language integrated learning approaches, using debates, discussions, and design-based tasks to foster creativity, linguistic fluency, and intercultural competence. The dual use of English – both in scientific (designer-to-designer) and conversational (designer-to-client) registers – demands a curriculum that addresses both academic and practical communication needs. Therefore, the research calls for strategic reforms, including curriculum realignment, increased exposure to authentic materials, faculty training in English for specific purposes, and the integration of project-based and blended learning. Thus, creative professional competence in foreign language is not a supplementary skill but a foundational one – essential for enabling designers to express innovation, collaborate globally, and adapt in a dynamic professional landscape. Systemic institutional support may find benefit from to realize these educational goals and prepare designers for 21st century challenges
Dividend policy in a crisis: a pre and post-COVID-19 comparison of DJIA and DAX companies
Full text linkThis study examines the shifts in dividend policy drivers for companies listed on the Dow Jones Industrial Average (DJIA) and Deutscher Aktienindex (DAX) by comparing the pre-COVID-19 (2015–2019) and post-COVID-19 (2020– 2024) periods. Employing a two-stage methodology, we first use factor analysis to distill traditional and cash flow-based profitability indicators into key factors, followed by panel regression models to assess their impact on dividend payouts. Findings indicate that the 2020 crisis significantly altered dividend strategies. For DJIA firms, dividend policy shifted from asset-based profitability (pre-2020) to a strong reliance on equity-based profitability (ROE, CFROE) post-2020, reflecting investor preference for immediate returns during uncertainty. For DAX firms, cash flow-based profitability emerged as the primary driver post-2020, unlike the pre-crisis period where no profitability factor was significant, highlighting distinct market responses to economic shocks in the U.S. and Germany
Analysis of the impact of passenger preparation on the throughput of security screening at airport checkpoints
No full textEfficient passenger screening is a critical component of airport security operations, directly influencing both safety standards and the overall passenger experience. As global air traffic continues to grow, optimizing the throughput of security checkpoints while maintaining regulatory compliance has become a major operational challenge. This study investigates one often overlooked factor affecting checkpoint performance – the level of passenger preparation prior to screening. The research combines experimental and simulation-based analyses to assess how improper passenger preparation contributes to the frequency of alarms at walk-through metal detectors (WTMDs). The study focuses on a security lane operating under a free passenger flow configuration equipped with a WTMD. The results demonstrate that better passenger preparation significantly improves checkpoint throughput and overall lane capacity. This microscopic analysis, which quantifies the operational impact of passenger behavior on system performance, addresses a gap not previously covered in the literature. The findings provide practical insights for airport security managers and system designers, emphasizing the importance of targeted passenger guidance and education in enhancing checkpoint efficiency
A horizon on the evolution of machine learning applications in real estate
No full textMachine learning (ML) in the real estate industry has transformed property assessment, administration, and promotion, tackling significant issues including market instability and pricing precision. Notwithstanding considerable progress in predictive, descriptive, prescriptive analytics, and automation, current research mostly emphasises technological and operational efficiencies, overlooking the integration of environmental, social, economic, and governance (ESEG) sustainability dimensions. This monitoring constrains the advancement of comprehensive and accountable real estate solutions corresponding to sustainable development objectives. This study aims to address these gaps by systematically analyzing publication trends, key contributors, and thematic clusters, incorporating sustainability principles via a combination of bibliometric and content analysis approaches. The study uncovers publication trends, key research themes, and their alignment with ESEG criteria. The results highlight significant research clusters in predictive and descriptive analytics while revealing a notable deficiency in sustainability-focused studies. Implications of this study underscore the necessity for incorporating ESEG dimensions into ML-driven real estate practices, promoting resilient, equitable, and environmentally responsible industry advancements. This study provides actionable insights for stakeholders to enhance sustainable ML adoption, fostering long-term viability and societal well-being in the real estate sector
Sludge-based catalysts for the remediation of PAH-contaminated sediments
No full textThe advanced persulfate oxidation method is known for its efficiency, stability, and capacity to breakdown organic contaminants without secondary contamination. In this study, biochar derived from sludge containing iron and manganese from domestic wastewater treatment was produced via pyrolysis and utilized to activate persulfate for the degradation of benzo(a)pyrene (BaP) in sediments. Results demonstrated that biochar pyrolyzed at 800 °C for 2 hours exhibited the highest catalytic performance. Under optimal conditions: a catalyst concentration of 1 g/L, persulfate concentration of 0.4 mM, and a reaction pH of 3, BaP removal efficiency reached 99.85% after 180 min. Characterization of the biochar showed that it was rich in Fe and Mn oxides, along with functional groups such as C-O-C, C=C, and C=O, which facilitated the adsorption and catalytic degradation of BaP. Quenching experiments revealed that the degradation of BaP was driven by reactive species such as •SO₄⁻ and •OH radicals, as well as singlet oxygen (¹O₂). The integration of radical dand non-radical pathways was essential for effective BaP removal. This research presents an innovative method for managing polycyclic aromatic hydrocarbons (PAHs) contamination in sediments by utilizing sludge-derived biochar in conjunction with activated persulfate