Journals Published by Vilnius Tech
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Foreign direct investment legislation and economic growth in Western Balkan countries: a panel analysis
Get PDFForeign direct investment (FDI) legislation plays a crucial role in fetching foreign investments. The objective of this study is to measure the impact of FDI on the Western Balkans countries (WBCs) and interpret the FDI law in the said countries. A panel data was obtained from the World Bank Indicators in order to conduct an empirical investigation. The sample is spread over twenty-eight years from 1995 to 2022. For econometric analysis, the study uses pooled ordinary least square (OLS), fixed effect (FE), random effect (RE), and Hausman test. The study also uses the Breuch and Pagan Lagrangian Multiplier test for Random Effect, the test for parameter constancy, the modified Wald test for groupwise heteroskedasticity, the Wooldridge test for autocorrelation, the test for serial correlation in residuals, and a test for normality. After a detailed analysis, the study concludes that FDI has a positive impact on the economic growth of WBCs. The study suggests that enforcing the rule of law on FDI will reduce the corruption index and create a favourable environment for WBCs to attract foreign investment.
First published online 17 March 202
Solutions of the attraction-repulsion-chemotaxis system with nonlinear diffusion
Get PDFIn this study, we consider the well-posedness of the attraction-repulsion chemotaxis system. This paper explores the dynamics of species movement in reaction to two chemically opposing substances, incorporating nonlinear diffusion. Our primary objective is to establish the existence of a global-in-time weak solution for the proposed model in an unbounded three-dimensional spatial domain. Our study has confirmed the existence of a global-in-time weak solution for the proposed system in three dimensions. Furthermore, we demonstrate that global-in-time weak solutions are also attainable for the proposed system in a bounded domain with a smooth boundary
On the stability and efficiency of high-order parallel algorithms for 3D wave problems
Get PDFIn this work, we investigate the stability conditions for four new high-order ADI type schemes proposed to solve 3D wave equations with a non-constant sound speed coefficient. This analysis is mainly based on the spectral method, therefore a basic benchmark problem is formulated with a constant sound speed coefficient. For a case of general non-constant coefficient the stability analysis is done by using the energy method. Our main conclusion states that the selected ADI type schemes use different factorization operators (mainly due to the need to approximate the artificial boundary conditions on the split time levels), but the general structure of the stability factors are similar for all schemes and thus the obtained CFL conditions are also very similar. The second goal is to compare the accuracy and efficiency of the selected ADI solvers. This analysis also includes parallel versions of these schemes. Two schemes are selected as the most effective and accurate
Exploring justice perceptions in online banking recovery: gender moderation and behavioral outcomes
Get PDFThe study addresses the recovery from service failures in online banking. It focuses on the three dimensions of perceived recovery justice – namely, distributive justice (DJ), procedural justice (PJ), and interactional justice (IJ) – and investigates their impact on post-recovery satisfaction (PRS), the moderating effect of gender, and further, the influences of PRS on customer trust (CT), affective commitment (AFFC), and customers’ behavioral intentions (CBI). The study uses partial least squares structural equation modelling to examine the data collected in Egypt from 445 respondents who experienced a service failure with online banking. The results show that the three dimensions of perceived recovery justice – DJ, PJ, IJ – exert positive influences on PRS, and gender moderates the effects of PJ and IJ on PRS: procedural justice makes women exhibit higher levels of PRS. In contrast, interactional justice makes men encounter higher levels of PRS. The results also show that PRS positively influences CBI through its direct and indirect effects (via CT and AFFC). Furthermore, PRS mediates the positive effects of DJ, PJ, and IJ on customers’ behavioral intentions. The study outcomes have significant theoretical and practical implications for online banking
The six-stage model of profitable growth and entrepreneurship in Finland: a Delphi study
Get PDFOur research has focused on addressing the following research questions for the growth strategies of SMEs: (1) What are the stages of profitable growth, and what factors contribute to these growth stages? (2) Which critical factors must be addressed for an organization to progress to the next stages of growth? (3) What is the importance of management in identifying and addressing critical growth factors? We have utilized the Delphi method and emphasized the role of company managers who have experienced profitable growth process as experts. Based on our findings, we have developed a Six-Stage Model of Profitable Growth (SSMPG), which we explain in detail in the article. The SSMPG model is compared to the prevailing Death Valley and Startup growth company development models. The article identifies the most crucial factors for the profitable growth of SMEs at different stages of growth within the SSMPG model. This model emphasizes sales, profitability, the individual characteristics of the entrepreneur, and leadership, in contrast to the debt-driven growth models emphasized in the other approaches. Further research could explore developing a start-up business culture using the new phasing model in Europe and elsewhere. In the future, it is important to consider profitability at both the company level and within clusters and regions
How macroeconomic factors impact residential real estate prices in Eastern Europe
Get PDF Purpose – This study examines how GDP growth, interest rates, and unemployment rates influence residential real estate prices in politically and economically stable Eastern Euro- pean countries, aiming to identify key drivers of property value changes in the region.
Research methodology – The study uses multiple linear regression and Pearson correlation (r) to assess the relationship between variables and housing prices, with ARIMA (3,1,0) applied for short-term price forecasts based on cyclical time series trends.
Findings – The findings show a strong correlation between macroeconomic indicators and residential real estate prices, with the key influencing factor varying by country, reflecting diverse market sensitivities and regional economic contexts.
Research limitations – The research is limited to Eastern European countries with stable political and economic conditions, excluding those facing instability. Future studies could expand the analysis to include such regions to provide a more comprehensive view.
Practical implications – The results provide valuable guidance for policymakers and investors in crafting strategies tailored to specific macroeconomic conditions, enhancing market predictions and stability.
Originality/Value – By focusing on the underexplored residential real estate market in Eastern Europe, this study contributes novel insights into regional housing price determinants and offers a foundation for further research on macroeconomic impacts in real estate markets
A literature review of common factors affecting labor productivity in Asia: 25 years of insight
Get PDFConstruction is one of the largest sectors of the Asian economy as it accounts for approximately 14.8% of Asia’s GDP. This, together with the fact that labor productivity is a key factor affecting project performance, makes enhancement of productivity a significant contributor to economic growth. Yet, previous studies have not provided a well-defined terminology together with an understanding of the prioritization of factors, which decision-makers need to take into consideration to enhance productivity in a structured manner. A structured literature review has been carried out, focusing on identifying factors affecting labor productivity in Asia, and calculating the aggregated rank. Hypothesis-testing revealed that the ranking could be generalized across the different regions in Asia. A full rank aggregation considering Asia as a whole reveals the five most important factors to be: “Incomplete design”, “Skill and experience (of laborers)”, “Competency of the project manager”, Materials”, and “Client and consultants”. Today’s research on factors affecting labor productivity is fragmented. By making a structured rank aggregation, and comparing findings between studies, a unifying understanding to the relative importance of factors affecting labor productivity has been established. The relative importance gives input to on-site mangers and helps enhancing managerial strategies to improve labor productivity
Mapping publications on value creation in construction project settings: a mixed bibliographic and bibliometric analysis
Get PDFThe worldwide interest on value creation has triggered an increasing number of articles, especially after a new paradigm named service-dominant logic was announced in 2004. However, limited research exists on the whole picture of value creation in the field of construction projects. Therefore, the current study is expected to reveal the status and future directions of value creation studies under construction projects. A number of 63 journal articles between 2004 and 2022 were analysed via a combined bibliographic and bibliometric approach, which covers annual publication, institutional and regional contribution, author contribution and keyword analyses. Results indicated that most published articles were based on the developed economies, such as the United Kingdom, Finland and Norway. Keywords such as megaproject, governance, social value and co-creation are emphasised, as analysed using CiteSpace software. Three implications, namely, value creation in developing areas, megaproject value creation, and perceived value perspective, are highlighted. The better understanding of the relevant literature could largely benefit academic peer researchers on value creation. Moreover, the holistic review of the literature body efficiently identifies the knowledge gaps and outlines avenues for following scholars and facilitating high-quality development of the construction engineering industry
Integration of BIM and ar with VSLAM to assist in construction site inspection
Get PDFBuilding Information Modeling (BIM) has been widely adopted for construction inspections due to its ability to integrate multiple data sources. Engineers use BIM to identify and review site issues, yet inspection systems face several challenges. Firstly, positioning inspection areas on a construction site using BIM with Augmented Reality (AR) requires complex model manipulation. Additionally, signal or Internet connectivity issues may limit positioning technologies. Secondly, human error or interference is common in traditional inspection processes due to their complexity.
To overcome these barriers, this research applied BIM and AR with Visual Simultaneous Localization and Mapping (VSLAM) to help inspectors quickly and effectively record construction defects as photographs with notes and their locations. An efficient approach is proposed to integrate BIM and AR with VSLAM, and a prototype is developed to validate and demonstrate how the proposed system can assist a site inspector in performing quality management, even offline. The system uses a two-phase indoor positioning method: initial localization via visual markers and real-time tracking with VSLAM, enabling precise defect tracking and efficient model adjustments. While significantly improving inspection accuracy and efficiency, its performance is affected by environmental factors like lighting and marker placement, providing insights for future refinement
Artificial intelligence as applied to classifying epoxy composites for aircraft
Get PDFThe problem of classification of epoxy composites used for the manufacture of aircraft structures is solved by machine learning methods: neural network, reinforced trees and random forests. Classification metrics were obtained for each method used. Parameters such as precision, recall, F1 score and support were determined. The neural network classifier demonstrated the highest results. Boosted trees and random forests showed slightly lower results than the neural network method. At the same time, the classification metrics were high enough in each case. Therefore, machine learning methods effectively classify epoxy composites. The results obtained are in good agreement with the experimental ones. The prediction accuracy score obtained using each method was greater than 0.88