Journals Published by Vilnius Tech
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Analyzing Helmholtz phenomena for mixed boundary values via graphically controlled contractions
Get PDFHelmholtz’s problem helps us to completely understand how sound behaves in a cylinder that is closed from one of its ends and opened at another. This paper aims to employ some novel convergence results to the Helmholtz problem with mixed boundary conditions and demonstrate the existence and uniqueness of the solution by applying graph-controlled contractions. For this purpose, we enunciate graphically Reich type and graphically Ćirić type contractions in the realm of graphical-controlled metric type spaces. In our study, we showcase the existence and uniqueness of fixed point results by employing these graphical contractions. This is demonstrated through extensive examples that a graphicalcontrolled metric-type space is distinct from traditional controlled metric-type spaces. We also exhibit an example of a graphically Reich contraction that is not a classical Reich contraction. Similarly, a decent example of graphical Ćirić contraction is presented, which is distinct from the classical Ćirić contraction. Concrete illustrative examples solidify our theoretical framework
Linking collaborative supplier social sustainability practices and supplier performance in asymmetric power relationships with buyers
Get PDFThis article objective is to identify factors related to collaborative supplier social sustainability practices and supplier international performance, and to propose a set of propositions regarding their relationships within a conceptual model. The research context includes manufacturing companies of various sizes located in Poland, which are predominantly Polish-owned and act as suppliers to large foreign buyers in relationships characterized by power asymmetry. The study determines which operationalizations of the main factors should be retained through factor extraction, evaluates their internal consistency using exploratory factor analysis, and validates the control variables. The conceptual model distinguishes between two areas of supplier collaboration on social sustainability practices: supply chain collaboration and horizontal collaboration. Future research may focus on examining the direct impact of these forms of collaboration on suppliers’ financial and non-financial performance in the context of their international operations
Digital economy and carbon emissions: spatial spillover effect and industrial structure mediation effect in China
Get PDFThe relationship between the digital economy and carbon emissions has emerged as a critical issue in the pursuit of the Sustainable Development Goals by 2030. This study examines the spatial spillover effects and the mediating role of industrial structure in this relationship using panel data from 285 prefecture-level cities in China between 2011 and 2022. Employing the Spatial Durbin Model (SDM) to capture spatial effects, stepwise regression and bootstrap tests for mediating effects, and the System Generalised Method of Moments (SYSGMM) to address endogeneity, the study reveals several key findings. First, the digital economy significantly increases carbon emissions with substantial spillover effects across regions. Second, carbon emissions exhibit both temporal and spatial dependence, influenced by time and location, with emissions in neighboring areas having a significant impact, leading to a “snowball” effect. Third, the digital economy indirectly elevates carbon emissions by optimizing industrial structures. These findings underscore the need for comprehensive strategies to manage carbon emissions effectively during economic transformation, aiming towards an environmentally sustainable economy.
First publihed online 02 April 202
Apartment prices, the business cycle and time on market: Evidence from Bucharest
Get PDFThe issue of time on market (TOM) correlation with the sale price remains under-explored considering the importance and complexity of the housing market. This paper argues that TOM is influenced by variables other than transaction prices and tests the hypothesis that the business cycle is important in explaining the dynamics of TOM and driving transaction prices in the housing market. In testing this hypothesis, the paper investigates the role of transaction prices and TOM in the housing market in Bucharest, Romania using granular observations of 32,000 price listings over the period 2013–2017, a time-scale that captures the economic recovery phase following the global financial crisis. The analysis shows that spatial correlation is strong for TOM rather than weak and that reinforcing spatial effects evidenced among TOM in transactions of closed units would reflect the strong clustering in prices but are balanced in a type of (contrary sign) distribution effect that diminish the whole spatial impact in TOM in similar size, describing a corrective mechanism leading to a more balanced impact on TOM. Results show that GDP affects transaction prices pro-cyclically (0.062%) and with persistence (0.054%), while only GDP growth (the cycle) influences TOM (0.352%)
Development drivers for urban regeneration and livability in worn-out neighborhoods
Get PDFDevelopment driver projects are recognized as tools for revitalizing and regenerating worn-out urban fabrics. Recent studies emphasize the importance of development driver projects for regeneration across three scales: macro, medium, and micro. However, research has lacked an examination of the impact of indicators at all three scales. To fill this research gap, the present study investigates the effect of development driver indicators on the regeneration of the worn-out fabric of Semnan, one of Iran’s historic and significant cities. This research initially identifies 16 indicators across the three scales. Data were collected from 385 residents and analyzed using the Phi coefficient and structural equation modeling. The results of the Phi test indicated that development projects could act as “nuclei for urban transformation of the worn-out fabric of Semnan”. Furthermore, the structural equation modeling analysis revealed that development driver indicators at the macro scale, such as parks (0.71) and landscape design (0.66), have a significant impact on regeneration. This study emphasizes the importance of a comprehensive approach to regeneration and suggests that active stakeholder participation in various stages of regeneration is essential. The findings of this study can serve as guidance for policymakers and urban planners in Iran and other countries
Double trouble: Time-varying connectedness between stock and housing markets
Get PDFJoint new records in the stock and housing markets are now gradually becoming a focal point of controversy in Taiwan. Based on the local heterogeneity of real estate assets, this study proposes setting up a two-market transmission mechanism between the stock and city-level housing markets to fully reply to this question. The estimation results using the Diebold-Yilmaz spillover method offer some critical information: the fact that the overheated housing market is precisely caused by the Taiwan stock market, which serves as evidence of the wealth effect. As far as the housing network is concerned, it is interesting to note that housing prices in Taipei as the source city spill out from near to far: New Taipei, Taichung and ultimately Kaohsiung. All these things make it clear that the authorities pay special attention to the status of the stock market as well as to inter-city differences in terms of housing spillovers
Multifractal analysis of Bitcoin price dynamics
Get PDFThis research employs Multifractal Detrended Fluctuation Analysis (MFDFA) to investigate multifractal properties in financial variables, including Bitcoin prices and economic indicators. Spanning 2019–2022, the analysis reveals multifractal scaling not only in Bitcoin prices, but also in economic indicators such as inflation rates and energy commodity prices. The non-linear singularity spectra unveil the multifaceted nature of scaling properties. Temporal analysis exposes intriguing trends in multifractality with implications for market efficiency. Furthermore, correlation analysis unveils connections among multifractal properties. For instance, a positive correlation between oil prices and Bitcoin suggests similar market forces. The log-log plot of fluctuation function Fq versus lag size demonstrates a power-law relationship, characteristic of multifractal systems. The empirical data’s alignment in log-log space suggests self-similarity in the Bitcoin time series, supporting multifractality. The calculated Hurst exponents values suggest varying degrees of multifractality across the years, with 2021 exhibiting the highest degree and 2022 the lowest. Furthermore, an asymmetry index (0.5767) deviating from 0.5 indicates that the multifractal nature of the Bitcoin market is not symmetric. This research enhances risk assessment and portfolio optimization in finance. It challenges the Efficient Market Hypothesis (EMH), emphasizing the significance of MFDFA in comprehending financial market and economic factor’s relationships
The influence of AI on price forecasting. The view of the academic community
Get PDFIn the context of the impressive development of Big Data, AI algorithms have proven their efficiency in processing and analyzing large volumes of data. Price prediction was no exception. In the modern economic fields, the need for advanced prediction models, with increased efficiency, has become more and more important. Thus, the interest in the potential of AI solutions in terms of price prediction for all industries has also grown progressively. The present study aims to capture, by using several Natural Language Processing techniques, the feeling that the academic community has in relation to the subject of price prediction and the way in which opinions have evolved over the years. For this purpose, the abstracts of the works indexed in the Clarivate WoS that addressed this topic are included in the current analysis. The scores obtained after the analysis reveal a slightly positive attitude towards the subject, but nevertheless quite reserved. The main topics existing in these articles are also extracted by means of Latent Dirichlet Allocation. Our analysis makes contributions to the formulation of the position that specialists in the scientific community have in relation to price prediction and AI evolution. Further, it provides new research directions for future studies
Determinants of AI adoption intention in SMEs. Romanian case study
Get PDFThe paper investigates the drivers and barriers that encourage or hinder the adoption of artificial intelligence (AI) technologies within Romanian SMEs. By using the Technology-Organisation-Environment (TOE) framework, we examined the role of several factors from each TOE dimension in predicting the AI adoption behaviour. The factors were constructed through factor analysis followed by the estimation of a linear regression model. Partial least squares structural equation modelling was then used in order to further explore the relationships and to check the robustness of the linear regression model. Our findings highlight the significant role played by leadership, organizational readiness, as well as the “push-and-pull” effect of competitors and customers in encouraging SMEs to adopt AI technologies. However, in the case of Romania, specific challenges related to a lack of digital skills among employees, a limited understanding of the relative advantage that digitalisation can offer, as well as a lack of marketing efforts from the side of vendors make it difficult for SMEs to consider the implementation of AI technologies. This exploratory study seeks to understand the underlying trends of the phenomenon and serves as a stepping stone for vendors, managers, as well as researchers to better understand the market for AI tools and solutions among Romanian SMEs
An analysis of the influence and mechanisms of the digital economy on the disparities in urban total factor productivity
Get PDFThe influence of the digital economy (DE) on the coordination of the urban total factor productivity (TFP) gap and its underlying mechanisms were investigated. The significance of this research mainly originates from its contribution to the theoretical understanding of regional coordination mechanisms, offering new insights into how the digital economy internally regulates disparities in regional TFP. Key findings include: (1) The dynamic analysis reveals that during the early stages of DE, the urban TFP gap expands significantly. However, as the digital economy matures, it contributes to reducing this gap. (2) Quantile regression results indicate that the digital economy substantially narrows the TFP gap primarily in regions with the most pronounced disparities (comprising 20% of the sample), while this effect is not evident in the remaining 80% of regions. (3) Enhancing the level of marketization of factors significantly strengthens the digital economy’s ability to reduce the TFP gap, and improvements in resource allocation also contribute to this effect.
First published online 06 June 202