Journals Published by Vilnius Tech
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A study on house price index performance: Mix adjustment and hierarchical linear growth repeat-sales models
Get PDFIn this study, we examined the differences between three house price indexes constructed using hedonic price, mix adjustment, and hierarchical linear growth repeat-sales modeling. The data consisted of housing sales across 13 administrative districts in Kaohsiung City from the third quarter of 2013 to 2022. The predictions were compared using the mean standard error, mean absolute percentage error, mean absolute error, and root-mean-square error. The results revealed that the hedonic price index performed the best; its prediction scores, as reflected by the four aforementioned metrics were 0.072, 1.176, 0.181, and 0.181, respectively. The index with the second best performance was the mix adjustment model, with scores of 0.154, 1.905, 0.293, and 0.293. The worst-performing index was the repeat-sales model, with scores of 0.309, 2.804, 0.439, and 0.439. After comparing the annual prediction errors of the three models, it became apparent that the hedonic price index had the best performance, followed by the mix adjustment index, and then the hierarchical linear growth repeat-sales index
On the impact of the COVID-19 pandemic on the household’s consumption and labor supply: theory and application
Get PDFThe COVID-19 pandemic and the corresponding regulation measures carried out to curb it have had a strong negative impact on the whole economy, and household consumption has been seriously affected. A large part of the drop in consumption is due to the reduction of household income, which is mainly caused by the labor supply loss during the pandemic. To present the mechanism of the impact of the pandemic on consumption, this study constructs a novel theoretical model. Two hypotheses about the pandemic’s impact on labor supply are proposed and empirically tested. Subsequently, a comparative static analysis is carried out to determine the numerical mechanism of the pandemic’s impact on household consumption. In addition, the model is also empirically tested and further modified for application, enabling the studies of both a realistic simulation and a policy simulation. This study finds that the labor supply of households has been affected during the pandemic, and there is a mediating effect channel through the regulation stringency. The epidemic severity and regulation policies have a negative impact on household consumption, in turn, will raise the saving rate of households. The income effect of the two on consumption accounts for 32% and 44% of the total effect respectively.
First published online 05 September 202
How big data development influences enterprise green technology innovation? The moderating role of digital inclusive finance
Get PDFExisting research thoroughly discussed the dividend effect of big data development (BDD), but few analyses have been conducted from a micro perspective of enterprises’ green development. With the exogenous policy shock of the National Big Data Comprehensive Pilot Zone, this study takes Chinese A-share listed companies as the research objects. We adopt the difference-in-differences model to systematically assess the impact of BDD on enterprise green technology innovation (GTI) and the moderating role played by digital inclusive finance (DIF) between the two. The study reveals that BDD significantly contributes to enterprise GTI. Furthermore, the facilitating effect of BDD on GTI is more significant in large enterprises, state-owned enterprises, enterprises with higher degrees of local government data openness, and enterprises with higher levels of the real economy. The moderating effect test shows that DIF significantly moderates BDD and enterprise GTI. Mechanism tests show that BDD promotes enterprise GTI through three channels: strengthening regional environmental regulation, alleviating enterprise financing constraints, and enhancing enterprise human capital. This paper provides valuable ideas for emerging economies planning to promote sustainable growth through BDD policies.
First published online 15 April 202
From theory to action: what motivates consumers to purchase IoT sustainable products
Get PDFIn an era marked by the importance of sustainability and technological integration, this paper explores the drivers behind sustainable consumption in a rapidly evolving market, focusing on Romanian consumer perspectives towards sustainable products driven by the relationship between the circular economy and the Internet of Things (IoT). Leveraging structural equation modelling, we conduct a thorough survey to investigate the roles of shaping purchase behaviors within the context of the circular economy and IoT integration. The findings reveal that while environmental attitudes significantly influence purchase intentions, price sensitivity and perceived value play a crucial role in shaping consumer choices. From a theoretical perspective, this study highlights the interplay between sustainability concerns and market dynamics, contributing to the broader understanding of sustainable purchase behavior. From a managerial perspective, the results provide actionable insights for businesses to design value-aligned strategies, ensuring that sustainable products are both accessible and appealing to a diverse consumer base. This dual focus on theory and practice offers a roadmap for fostering responsible consumption in a competitive marketplace
How does environmental tax reform drive corporate innovation to green technologies? Quasi-natural experimental evidence from China
Get PDFHow to motivate enterprises to formulate green technology (GT) innovation is crucial for promoting green development and minimizing pollution control costs. This research employs a quasi-experimental approach to analyze the impact of environmental tax reform (ETR) on corporate innovation decisions. First, we construct a two-sector model within a single enterprise, where the enterprise produces goods using GT and non-green technology (NGT) respectively. ETR influences a company’s innovation choices by the relative market value, R&D intensity, and productivity of products manufactured using GT and NGT under profit maximization. Second, we test our model using 20122023 manufacturing firms’ data, and the empirical results confirm our theoretical predictions. Third, we perform robustness tests to exclude the impact of subsidies, command and control environmental supervision and the COVID-19 epidemic. Fourth, we conduct heterogeneity analysis in polluting level and market competition. Finally, this study uses two instrumental variables (IVs) to validate our main regression results: the interaction between regional water area and industrial chemical oxygen demand, and the proportion of days affected by temperature inversion. This study contributes to the literature related to innovation choices under environmental policy and has implications for directing firms’ innovation to GT
Exploring spatial programming through modularity based evolutionary computation
Get PDFThe application of evolutionary computing in architecture has advanced beyond active feedback to designers by integrating natural processes with computation to synchronize input from the final solution. Following knowledge in digital morphogenesis, new approaches can be formed by examining design issues deemed non-pragmatic and abstract, such as function in spatial programming. The study presented in this paper explores an approach based on the principle of modularity, which describes a biological system’s ability to organize distinct, independent units to increase the system’s adaptability. By employing modularity in evolutionary computation, we can characterize function as an abstract feature of phenotypes. The basic modularity method is simulated by developing a spatial program with dynamic programmatic functions to see how adaptable units are as spatial program components
Bibliometric analysis of digital financial reporting: a comprehensive review of research trends and emerging topics
Get PDFDigital Financial Reporting (DFR) has gained significant research attention amid the digital transformation. This study comprehensively reviews DFR research, identifies trends, and highlights emerging topics. Key trends include advancements in sustainability reporting and improved financial reporting quality while emerging topics like XBRL and International Financial Reporting Standards (IFRS) reflect evolving research interests. Utilizing bibliometric methods, the study quantitatively analyzes DFR literature from Scopus, Emerald, Google Scholar, OpenAlex, Crossref, and SAGE. The research involved data sourcing, screening, eligibility selection, and bibliometric analysis. Findings show a dynamic increase in annual publications in DFR, with noticeable peaks and shifts in research focus over time. A notable rise post-2016 culminated in a peak in 2023, indicating sustained scholarly interest and field evolution. This study contributed into how digitalization enhances financial reporting quality, addressing gaps from previous bibliometric analyses. It emphasizes systematic trend analysis, identifying research gaps, and exploring factors driving the digital transformation of financial reporting. These insights guide researchers in developing new variables and strategies to advance DFR solutions, enhancing the accuracy, transparency, and accessibility of financial information through digital innovation
Assessment of causal relationship amid enablers of successful transition of management succession in family-owned businesses – a study of the South Asian Nations
Get PDFThe present study was done to evaluate the causal relationship amid the enablers of successful transition of management succession in family-owned business in South Asian Nations. This was an empirical study where owners of family-run business across various South Asian countries were interviewed. In this study we used the Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach to examine the causal relationship among the twelve variables which were identified by examining the existing literature. The findings of the research demonstrated that formal education, well defined succession plan, early affiliation in business etc. formed the cause group and shared vision for future, active involvement of the successor/s in the succession process, tacit knowledge transfer, building trust and credibility in successors and competence over gender etc. formed the effect group
The impact of building information modeling on reducing greenhouse gases through design validation
Get PDFThis study proposes a method to reduce rework due to design errors by applying building information modeling (BIM) to reduce greenhouse gas (GHG) emissions during the construction stage. The study focuses on reducing waste in construction materials, transportation, and recycling, with the analysis grounded on expert opinions using fuzzy theory and life cycle inventory data. Applying the proposed method to the case building reduced emissions by 113,211 kg CO2eq, which is 64 times the GHGs emissions from driving a car or van for 10 or fewer passengers over 20,000 km. To offset 113,211 kg CO2eq, about 12,441–13,977 pine trees would be required. Reducing wasted concrete contributes to approximately 79.9% of the total GHGs emissions decrease. Among the buildings that started construction in South Korea between July 2022 and February 2023, 68.3% are reinforced concrete structures based on gross floor area. Applying BIM to these structures could yield even greater benefits than those reported in this study. This study also introduces a method based on fuzzy analytic hierarchy process (AHP) for decision makers to prioritize design changes. This method provides quantitative data to enrich qualitative discussions among construction, BIM, and estimation managers regarding design changes
Journal of Civil Engineering and Management: contribution to development and application of MCDM methods in construction management
Get PDFMulti-criteria decision-making (MCDM) methods have improved considerably since the 1970s and are applied in many fields, demonstrating that the field of decision research remains important and valuable. Multi-criteria methods contribute to the research in civil engineering and construction management by identifying the optimal alternatives considering conflicting objectives. Researchers are applying MCDM methods in specific areas of civil engineering to resolve conflicts between economic, environmental and technological criteria. On the occasion of the 80th birthday of Prof. E. K. Zavadskas and 30 years of the Journal of Civil Engineering and Management (JCEM), this article aims to summarize the performance indicators of JCEM and its contribution to the development and application of MCDM methods in construction management. The journal’s performance indicators are outlined using bibliometric analysis