Journals Published by Vilnius Tech
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Study on the polymeric treatment with rice husk silica on sisal fiber in cementicious composites
Get PDFThis research evaluates how treating sisal fibers with expanded polystyrene (EPS) and rice husk silica (RHS) affects their absorption capacity, tensile strength, and adhesion when used in Portland cement matrices. The study on sisal fibers treated with EPS and RHS polymers found that the treatment significantly reduced water absorption by 70%, from 84.67% for untreated fibers to 15.18% for treated ones, due to the hydrophobic nature of EPS. Optical microscopy revealed an irregular polymer layer on the fibers, which, while improving dimensional stability, could impair fiber-matrix interaction. Despite these improvements, the treatment did not notably enhance the mechanical properties of the fibers, as the breaking strength remained similar to untreated fibers, and the rupture displacement slightly decreased
Land purchasing behavior of real estate enterprises: An organizational status perspective
Get PDFBased on resource dependency and signaling theories, this study examines how organizational status affects land purchasing behavior in listed real estate enterprises on China’s Shanghai and Shenzhen A-shares from 2006 to 2023. The findings indicate that the organizational status of real estate enterprises positively impacts their land purchase area, price, and quantity. Further analysis reveals that managerial overconfidence mediates this relationship. Heterogeneity analysis shows that the organizational status of state-owned real estate enterprises positively influences all three types of land purchasing behaviors, while for non-state-owned enterprises, it only significantly affects the area and price of land purchases, not the quantity. This study enriches the theory on land purchasing behavior of real estate enterprises, expands the application scope of organizational status, reveals the mechanisms through which organizational status affects land purchasing behavior and provides valuable insights for guiding rational competition among real estate enterprises, optimizing land resource utilization, and promoting the healthy and sustainable development of the real estate industry
Bitcoin: a Ponzi scheme or an emerging inflation-fighting asset?
Get PDFUnder the dual impact of the COVID-19 pandemic and the Russian-Ukrainian conflict, the excessive stimulation of monetary policy continuously pushes up global inflation (INF). Therefore, this article explores whether Bitcoin can serve as a safe haven for INF. We apply the rolling-window Granger causality test to solve the issue of parameter instability in vector autoregression (VAR) systems and investigate the time-varying interaction between INF and Bitcoin price (BP). The negative influence of INF on BP means a high inflation shock causes BP to decline, indicating that Bitcoin cannot be a safe asset against INF. This is because investors have decreased their willingness to hold Bitcoin under the high INF expectations and cause BP to fall. This finding is not supported by the Intertemporal Capital Asset Pricing Model, emphasising that INF positively impacts BP. Conversely, BP has positive and negative impacts on INF. The positive effect highlights the effectiveness of Bitcoin in predicting INF fluctuations, but economic factors could undermine this effectiveness. In the context of economic stagnation and market turmoil, investors can adjust their portfolio investments based on Bitcoin. The government should utilise the trend of BP to regulate the dynamics of INF to reduce uncertainty in the financial system.
First published online 30 August 202
Debt or equity? Financial impacts of R&D support across firm demographics
Get PDFThis study utilizes data from Korea’s Research and Development (R&D) grant program to examine the impact of receiving an R&D grant on a firm’s ability to obtain external financing, taking into account the heterogeneous effects based on firm size and characteristics. By employing the propensity score matching method, we establish the causal effect of R&D support on financing and discover that R&D grants have differential effects on debt and equity financing. Our findings indicate that larger firms are more likely to acquire subsequent debt financing, whereas small firms that receive R&D grants exhibit an increased likelihood of securing equity financing, particularly among young firms. Furthermore, we identify a certification effect of R&D grants, implying that such grants may serve as indicators of the potential success of small, young firms in the market. Collectively, this study illuminates the role of R&D grants in firms’ financing decisions, providing valuable insights for policymakers and firms seeking to secure external financing.
First published online 12 December 202
Is the process of graduation of least developed countries (LDCS) suitable and sufficient?
Get PDFMillions of people are living in the Least Developed Countries (LDCs), the poorest of the poor. Getting them out of that situation is one of humanity’s most urgent tasks. Since 1971, the United Nations has recognized LDCs as a category of countries characterized by, among others, dependence on international trade, rapid population growth, low literacy, an unskilled labor force and poorly developed institutions. This research analyzes the patterns in the evolution of a group of LDCs that have led them to graduation. This paper assesses whether the established way to leave this group of countries is realistic and foundational for future progress. The paper is organized as follows: Section 1 is a brief introduction on LDCs and their characteristics, Section 2 presents the method applied to obtain the results, focusing on criteria that must be met; Section 3 provides the results for the countries in the graduation process; Section 4 includes a discussion and comments on the results; Section 5 summarizes the main findings and draws conclusions. Additionally, a bibliographical review of the literature consulted is provided.
First published online 18 March 202
GDP per capita vs foreign direct investment: key drivers of a country\u27s technological leadership
Get PDFThis study aims to test the hypothesis that countries with high GDP per capita achieve technological leadership not primarily due to their domestic production capacity but through the inflow of foreign direct investment (FDI). The research covers 21 developed countries across Western Europe, the Americas, Asia, Africa, and Australia, for the period 2011 to 2022. The Bartlett test, Kaiser-Meyer-Olkin (KMO) criterion, and exploratory factor analysis (EFA) were employed to identify the most relevant indicators for the study. A true fixed-effects stochastic frontier model was applied to panel data, based on the Cobb-Doug- las production function and the translogarithmic function, to evaluate the determinants of technological development and identify technical efficiency. Fourteen indicators of techno- logical development were used as independent variables, while five key economic indicators were included as adjustment variables. Research and development expenditure served as the dependent variable. Three frontier models were constructed, incorporating adjustment variables such as GDP per capita, FDI net inflows, and FDI net outflows. The findings provide valuable insights for reviewing the key determinants of technological development management in economically advanced countries.
First published online 17 March 202
Identification of risk factors: a comparison of conventional and Islamic stocks
Get PDFThe study identifies the difference in the long-run risk factors for Conventional Capital Market (CCM) and Islamic Capital Market (ICM) in the post-Shari’ah-screening era in an emerging market. The sample includes macroeconomic variables representing the real sector (industrial production), money market (interest rate), international market (exchange rate) and external sector (exports and workers’ remittances) and two market indexes for 164 Months (01/10–08/23). Johansen cointegration and Granger causality tests are applied to document the evidence. Results support the integration of market indexes with macroeconomic indicators; however, market indexes lack mutual integration in the long run. The integrated group of variables differs slightly for ICM (exchange rate and industrial production) and CCM (industrial production). The real sector activity is reflected in the market, while the monetary sector is missing. The behaviour of the Islamic market is in line with the theory – a reflection of the real sector and lack of integration with interest rates. We recommend three policy actions, including improved facilitation of industrial production, prudent management of exchange rate, and a balanced monetary policy, as theory suggests the usefulness of stock indicators for monetary policymaking. The comparative study on macroeconomic risk factors in an emerging market enhances the understanding of a market with dual indexes, including CCM and ICM.
First published online 31 March 202
A hybrid clustering and boosting tree feature selection (CBTFS) method for credit risk assessment with high-dimensionality
Get PDFTo solve the high-dimensional issue in credit risk assessment, a hybrid clustering and boosting tree feature selection method is proposed. In the hybrid methodology, an improved minimum spanning tree model is first used to remove redundant and irrelevant features. Then three embedded feature selection approaches (i.e., Random Forest, XGBoost, and AdaBoost) are used to further enhance the feature-ranking efficiency and obtain better prediction performance by applying the optimal features. For verification purpose, two real-world credit datasets are used to demonstrate the effectiveness of the proposed hybrid clustering and boosting tree feature selection (CBTFS) methodology. Experimental results demonstrated that the proposed method is superior to others classic feature selection methods. This indicates that the proposed hybrid clustering and boosting tree feature selection method can be used as a promising tool for solving high-dimensional issue in credit risk assessment.
First published online 12 February 202
From uncertainty to opportunity: financial development as bridge to green innovation under economic policy uncertainty
Get PDFGreen innovation (GI) is increasingly recognized as an essential strategy for tackling urgent environmental issues, such as climate change, resource depletion, and pollution. While research is expanding on how economic policy uncertainty (EPU) affects GI, the influence of financial sector development (FSD) as a moderator in this context remains under-examined. To address this gap, we conduct an empirical analysis utilizing two decades of data (2000–2019) from five major emerging economies (BRICS). The study employs FMOLS and DOLS models to scrutinize the data. The findings indicate that EPU has a considerable adverse effect on GI, suggesting that uncertainty in economic policies can obstruct environmentally sustainable progress. In contrast, FSD demonstrates a notable positive association with green innovation, indicating that a robust financial sector can support and bolster these initiatives. Furthermore, the study identifies that FSD serves a crucial intermediary function in the EPU-GI connection. The policy implications of this study are significant, indicating that decision-makers should prioritize enhancing financial sector institutions to foster GI, particularly in times of heightened economic volatility. By providing new evidence regarding the dynamics between EPU, FSD, and GI, this investigation offers valuable insights for developing policies that harmonize economic stability with environmental sustainability.
First published online 1 April 202
Does government digitization contribute to economic growth? Empirical evidence from 109 countries
Get PDFIn the digital age, governments worldwide are increasingly turning to digitization to enhance efficiency and foster economic growth. This study investigates the impact of government digitization on economic growth, addressing the pressing issue of how digital transformations within the public sector can drive economic growth. First, we empirically estimate panel data from 2002 to 2021 across 109 countries using multiple statistical methods, consistently supporting that government digitization can significantly promote economic growth. Subsequently, mechanism tests are conducted using two fixed effect models containing interaction terms, revealing that government digitization can foster economic growth by curbing corruption and reducing the time businesses need to access public services. Furthermore, heterogeneity analysis confirms the moderating effects of telecommunications infrastructure, basic education popularization, natural resource abundance, government efficiency, democracy, and ruling party ideology on the relationship between government digitization and economic growth. Lastly, quantile regression reveals a nuanced pattern, indicating that as a country’s economic development level increases, the promoting effect of government digitization on economic growth initially rises before declining. These findings provide new insights for governments worldwide seeking economic growth.
First published online 04 July 202