Journals Published by Vilnius Tech
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Data-based flight optimization model for scheduling: noise management approach
Get PDFCivil aviation noise remains a key challenge that limits the industry’s growth. With the rise in global air traffic, aviation noise pollution is becoming an increasingly pressing concern. This research develops a data-driven flight optimization model to mitigate noise levels at Vilnius Airport. The research is conducted in three stages: first, existing noise reduction strategies and the potential of scheduling optimization tools are reviewed. Next, EUROCONTROL’s integrated aircraft noise and emissions modelling platform is used to assess noise levels for each flight operation under relevant atmospheric conditions. Finally, a flight schedule optimization model is developed by considering key variables, constraints, and assumptions affecting airport noise, followed by an evaluation of its performance and efficiency. The findings suggest that effective noise management requires a comprehensive approach, integrating operational adjustments with a detailed understanding of industry factors
Above-building parking area and urban plan arrangement proposal for civil aircraft: the case of Türkiye
Get PDFThis study examines the feasibility of integrating vertical take-off and landing (VTOL) civil aircraft into urban environments in Türkiye, with a focus on adapting existing building structures and urban planning regulations. The research investigates the structural, legislative, and urban design modifications needed to support the safe operation of personal and family-use VTOL vehicles. Case studies from Istanbul, Ankara, Izmir, Diyarbakır, and Samsun highlight the challenges and opportunities posed by both old, unplanned urban areas and newer, systematically developed regions. The findings reveal the need for significant legal reforms, including updates to civil aviation regulations, and structural adjustments such as rooftop reinforcements to support VTOL operations. The study emphasizes that incorporating aircraft-friendly infrastructure in new urban developments is more cost-effective than retrofitting existing buildings. It also highlights the importance of creating dedicated take-off, landing, and parking areas within urban spaces to accommodate the growing demand for urban air mobility. The research concludes that proactive urban planning, legislative changes, and technological innovation are critical for fostering sustainable urban air mobility, enhancing transportation efficiency, and ensuring safety in Türkiye’s evolving urban landscapes
Adapting to uncertainty: A quantitative investment decision model with investor sentiment and attention analysis
Get PDFIn the face of global uncertainties, including pandemics, economic fluctuations, disruptions in supply chains, major disasters, wars, and impending economic crises, the financial landscape and the impact of investor sentiment on the return of stock index futures can be significantly altered. Understanding the relationship between investor sentiment, attention, and stock index futures returns in the face of these diverse challenges has become particularly critical. However, existing research does not adequately consider the effect of these unexpected events on the market and the shifts in investor attention. Using the COVID-19 pandemic as a case study, this research proposes a dynamic quantitative investment decision-making model that considers the influence of investors’ attention and emotional characteristics, aiming to adapt to the financial market under these global changes and improve the accuracy of quantitative investment forecasting. Initially, the Bidirectional Encoder Representations from Transformers model is employed to analyze investor comment data, extract information on investor attention and emotional characteristics, and construct investor sentiment indicators. Subsequently, a stock index futures forecasting method based on Variational Mode Decomposition algorithm and Support Vector Regression (SVR) model is constructed, and the grey wolf optimization algorithm is introduced to optimize the parameters of the SVR model. Guided by investor sentiment indicators, different market states are further distinguished, and appropriate investment strategies are implemented to effectively enhance the returns of quantitative investment. When compared with models that neglect investor attention and emotional characteristics, the results show that considering investor sentiment indicators not only improves the predictive ability of the model, but also reduces cognitive bias and market risk.
First published online 6 December 202
Unveiling the impact of improvement methodologies on employee engagement: Insights from central European companies
Get PDFImprovement methodologies (IMs) consist of many components; however, employee engagement (EE) is particularly important in bottom-up initiated process improvement. This study aims to investigate EE with reference to IMs used by companies. EE measurement constructs focused on process improvement has been developed and verified as reliable. This study examines a sample of 380 medium- and large-sized companies. The ANOVA procedure proves that: (1) IMs support EE in companies, and (2) the absence of IMs leads to lower EE. However, support for EE is specific and does not primarily concern issues directly related to process improvement. This study also discovers the multi-use of IMs by companies. IMs such as Lean, strongly focused on EE by their assumptions, only moderately support EE in companies. The study found no exceptionally effective IM which allows for the easy gain of EE in the investigated companies’ current state of implementation. The results imply that companies are approximately halfway towards the effective use of IMs. They should rethink the use of IMs, transform their leadership style, and better motivate employees to engage in bottom-up process improvement, which is indispensable.
First published online 18 November 202
Educational efficiency and technology skill development: a cross-income country analysis
Get PDFThe relationship between educational efficiency, technology proficiency, and economic development remains a subject of debate, with existing empirical studies producing mixed results. Our study aims to clarify this association by investigating how advancements in technology skills can enhance educational outcomes and, in turn, stimulate economic growth. We employ a dynamic panel model with fixed effects, utilizing data from 2009 to 2022 that covers 23 lower-income, 23 middle-income, and 18 higher-income countries. Our findings reveal a significant positive impact of educational efficiency and technology proficiency on economic development, particularly in low-income countries, where the synergy between these factors drives accelerated growth. In higher-income countries, the influence of educational efficiency appears minimal, but the persistent benefits of technological competencies emphasize the critical role of technology in sustaining economic progress. Robustness checks affirm the strength of these results, leading to actionable policy recommendations that prioritize investments in education and technology to foster sustainable economic development across diverse income groups.
First published online 05 June 202
Fuel prices and economic activity: time and frequency analysis for selected European countries
Get PDFThe effects of fuel prices on economic activity are still being investigated, as oil and gas are critical inputs in the production process. This study examines the relationship between fuel prices and macroeconomic aggregates both in the time domain and frequency domain in three selected countries of Germany and Poland as net oil importers and Norway as a net oil exporter for the period 1995Q1–2021Q3. The causal relationships between these macroeconomic variables are first examined using a conventional Granger causality test for the time domain and then the Breiutung–Candelon test based on the vector autoregression model for the frequency domain, which are estimated separately for the long-term, business cycle, and short-term components obtained by applying the boosted Hodrick–Prescott filter. This study demonstrates that the predictability of fuel prices for macroeconomic aggregates differs across various frequencies. Although the patterns of causality differ across countries depending on whether it is oil-importing or oil-exporting and the level of economic development and energy mix, this relationship is found to be important for slowly and fast fluctuating components but to different degrees in each country.
First published online 15 April 202
Decoding tourist satisfaction for sustainable economic development: a multi-method configuration framework using online reviews
Get PDFOnline reviews are crucial to understanding tourist satisfaction (TSA) in the digital tourism era. This study deconstructs the factors leading to high TSA performance in reviews, offering guidance for long-term economic benefits for destinations and businesses. Building on the three-factor theory, we create a framework utilizing text mining, affective distribution computing, and fuzzy-set qualitative comparative analysis (fsQCA) to identify patterns driving high TSA. We employ topic modeling to extract destination attributes from reviews, quantifying their performance through affective distribution computing. An enhanced Kano model classifies tourist needs based on emotional expressions in reviews. We investigate how basic, performance and excitement attributes interact and influence TSA. Additionally, we apply the coupling coordination degree model (CCDM) to analyze attribute interconnections within configurations. Our results show that no single attribute leads to specific outcomes; relatively, high TSA results from a combination of attributes. This study identifies three normative causal recipes and is the first to clarify the complex interactions in satisfaction management within the three-factor theory framework, addressing a significant knowledge gap. Ultimately, our operational guidelines aim to sustain the economic vitality of the tourism industry.
First published online 14 July 202
Classification and identification of medical insurance fraud: a case-based reasoning approach
Get PDFAppropriate classification of medical insurance fraud events can not only be effective in preventing and combating fraud, but also greatly improve the utilization of medical resources. Due to the uncertainty inherent in medical insurance fraud, identifying and classifying the fraud are non-trivial tasks. In addition, the selection of classification radius by traditional methods is often highly subjective. To this end, a case-based reasoning (CBR) approach in probabilistic hesitant fuzzy environment and its application to classifying the severity of medical insurance fraud events are investigated in this article. At first, the probabilistic hesitant fuzzy element (PHFE) is regarded as a discrete probability distribution, and its distribution function is defined. On this basis, a distribution discrepancy degree is proposed to make up for the shortage of existing measures between PHFEs. Then, a probabilistic hesitant fuzzy decision-making method based on CBR is proposed, which considers both decision data and the expert’s own knowledge and experience. Finally, the proposed method is used to classify the severity of medical insurance fraud events, and the rationality and superiority of the method are verified by comparative analysis.
First published online 15 July 202
Strategic modeling of enterprise business processes for successful digital transformation
Get PDFPurpose – the purpose of this study is to develop a methodology for modelling business processes based on the principles of process management and the use of modern information technology in order to improve the efficiency and quality of the enterprise.
Research methodology – in this work we applied the methodology of business process analysis and optimisation based on the decomposition principle proposed by the SADT methodology. Findings – the result of the study was the development of practical recommendations for enterprises seeking to improve the efficiency of their activities and adapt to rapidly changing market conditions. The proposed methodology of business process modeling allows organi- zations not only to standardize and optimize their processes, but also to respond flexibly to changes in the external environment and maintain competitiveness.
Research limitations – The study focuses primarily on SADT and IDEF0 methodologies, which may limit consideration of other potentially effective approaches to business process mode- ling. Future research may include a comparative analysis of different business process modeling methodologies to determine their relative effectiveness and applicability in different contexts.
Practical implications – overall, this study makes a significant contribution to the development of modern business process modeling methodology, providing practical tools and recommendations for organizations seeking to improve their performance and sustainability in a rapidly changing business environment.
Originality/Value – the novelty of this study lies in the development of an integrated methodology of business process modeling based on the principles of process management and modern information technologies. In contrast to earlier studies emphasizing individual aspects of process management or specific technologies, our study offers an integrated approach combining both managerial and technological elements
Applying the mean-variance framework: portfolio optimization and comparative performance analysis in the emerging Colombian capital market
Get PDFPurpose – this paper adopts the mean-variance approach in optimizing portfolios within the Colombian capital market, a setting full of complications such as lack of liquidity and market concentration. It delivers actionable messages for emerging market stakeholders and formulates guidance aimed at enhancing risk-adjusted returns and informing portfolio management in markets with similar structural and economic conditions.
Research methodology – a bi-objective mean-variance model has been used for analyzing the stock prices of 17 stocks on a weekly basis from 2009–2024. Annual rebalancing has made the portfolio responsive to changes in the market, considering the Sharpe ratio as the benchmark to assess risk-adjusted performance.
Findings – optimized portfolios in Colombia outperformed traditional investment funds by realizing better returns while having a balanced risk. Surely, this shows that the model is able to be flexible and react to changes in fluctuation, capture sectoral opportunities, and perform amazingly in a dynamic market.
Research limitations – focusing on adaptability and real-time rebalancing in this work can establish a basis on which future research will operate, refining optimization strategies that incorporate advanced risk measures such as CVaR.
Practical implications – the results present an effective and flexible tool for investors to optimize their portfolios in respect of risk diversification and sustainable returns, considering liquidity constraints and market turmoil.
Originality/Value – this research connects theory and practice and demonstrates the flexibility of the mean-variance model in emerging economies. It emphasizes novelty in portfolio optimization solutions and further development of strategies in sophisticated financial conditions