Research on convergence deals with the question of whether regional disparities are decreasing over time. Aiming to decompose EU disparities covering regions of all levels, this paper fills the gap of the empirical research on convergence in the EU in the following ways: (i) the research updates the assessment of regional disparities in the EU emphasizing, but not limited to, the analysis at the NUTS 3 level; (ii) based on a constructed three-level Theil index, the research decomposes EU disparities into between-country, within-country at the NUTS 2 level, and within the NUTS 2 region at the NUTS 3 level components, covering the period of 1995-2014 and all EU regions, (iii) it examines the linkages between the development of innovation and technology, sustainability, and evolution of disparities. Our main findings suggest that convergence in the EU is still present at different regional levels, but its speed is slowing down. Total EU disparities were decreasing mainly because of reducing disparities between member states. At the same time, in the majority of EU member states, old and new, within-country disparities were growing at all regional levels, and now within-country disparities account for almost two-fifths of total EU disparities.

Abstract:The aim of this article is to enhance the understanding of how design companies perceive the benefits of Building Information Modeling (BIM) technologies application. BIM is recognized in the literature as a (potentially) powerful driver leading the construction sector towards sustainability. However, for design companies, the choice to invest in BIM technologies is basically an economic one. Specifically, a design company assesses economic benefits and efficiency improvements thanks to the application of BIM technologies. The article discusses the return on investments (ROI) in BIM technologies and reviews ROI calculation methodologies proposed by other authors. In order to evaluate BIM return on investment correctly practical ROI calculations are carried out. Appropriate methods, together with the relevant variables for ROI calculation, are developed. The study allows for adjusting the calculation method making it more accurate and understandable using the Autodesk Revit based ROI calculation of the first year.

Currently countries are facing a new crisis caused by the COVID-19, which leads to the rise of government expenditures and additional borrowing. This situation highlights the importance of examine factors which determine the level of public debt that still sustains economic growth. A growing body of research supports the idea of a non-linear debt–growth relationship and estimates the threshold level above which debt becomes unsustainable and has a negative effect on output. The empirical evidence points out that there is no single sustainable debt threshold level that holds for all countries. This research complements scarce empirical evidence on the heterogeneous debt–growth relationship and provides some insights on the publicly available statistical indicators that might signal a relatively low/high expenditure multiplier and, at the same time, potentially unsustainable/sustainable growth stimulus through the use of borrowed funds. We test the hypothesis that the expenditure multiplier is shaping the impact of public debt on growth. Our empirical examination is based on panel data analysis in the groups of countries with expected relatively high and low expenditure multiplier. Research results show that a statistically significant negative marginal effect of debt on growth starts to manifest at a lower debt-to-GDP ratio when the expenditure multiplier is lower and vice-versa. The study shed some light on the sources of heterogeneity in a debt–growth relationship. We can conclude that countries with a high expenditure multiplier level can borrow more and sustain growth. In contrast, in countries with a lower expenditure multiplier, a relatively low debt level becomes unsustainable for growth.

ĮvadasDinamiškomis ir konkurencingomis rinkos ekonomikos sąlygomis verslą nuolat lydi neapibrėžtumas ir rizikingi sprendimai. Įmonių bankrotai šiame kontekste tapo neišvengiamu reiškiniu, kurio mindaugas bUTKUS, Sigita ŽAKARė, Diana cIbUlSKIENė bankroto diagnostikos modelis ir jo pritaikymas bankroto tikimybei lietuvos įmonėse prognozuotiBankroto tikimybės prognozavimas pripažįstamas kertiniu norint išvengti šio reiškinio ir jo sukeliamų pasekmių. Bankroto tikimybės prognozavimui siūlomi skirtingi modeliai, tačiau, moksliniai tyrimai patvirtina, kad jie nėra pilnai tinkami Lietuvos įmonėms. Šiame straipsnyje pristatomas modelis, grindžiamas binomine logistine regresija, skirtas prognozuoti bankroto tikimybę Lietuvos įmonėse.Raktiniai žodžiai: bankrotas, prognozavimas, logistinė regresija.Bankruptcy likelihood prediction is recognized as a cornerstone to avoid it and it's consequences. Different models are offered to predict company's bankruptcy likelihood, but scientific researches confirm that they are not fully suitable for Lithuanian companies. This article presents the model based on the binomial logistic regression to predict company's bankruptcy likelihood in Lithuania.Keywords: bankruptcy, prediction, logistic regression.JEL Classifications: C25/C55/G33.pasekmės tampa ne tik pačių įmonių problema, bet lemia ir bendrą šalies ekonomikos vystymosi raidą. Šis procesas atlieka svarbias funkcijas šalies ekonominiame gyvenime, kadangi su veiklos sunkumais susiduriančios įmonės ieško naujų būdų savo veiklos tobulinimui, o iš rinkos natūraliai mindaugas bUTKUS, Sigita ŽAKARė, Diana cIbUlSKIENė 112 pašalinami neefektyvūs jos dalyviai, skatinama konkurencija. Bankroto tikimybės prognozavimas, jo grėsmės numatymas pripažįstami kertiniais elementais sprendžiant įmonės bankroto problemą. Siekiant išvengti įmonės bankroto ir jo sukeliamų pasekmių, svarbu turėti veiklos stabilumo ir tęstinumo vertinimo modelį, kuris padėtų nustatyti iškilu-sias finansines problemas gerokai anksčiau, nei paaiškėja, kad įmonė yra nemoki ir jai gresia bankroto byla.Įmonės bankroto prevencijai įvairūs mokslininkai pasiūlė daug skirtingų bankroto tikimybės prognozavimo modelių, tačiau, moksliniai tyrimai patvirtina, kad jie nėra vienareikšmiškai tinkami Lietuvos įmonių nemokumui vertinti (Tvaronavičienė, 2001;Buškevičiūtė, Mačerinskienė, 2002;Stundžienė, Boguslauskas, 2006; Garškaitė, 2008 ir kt.). Tiek Lietuvos, tiek užsienio mokslininkų tyrimuose akcentuojamas naujų specifinių įmonės bankroto tikimybės prognozavimo modelių, pateikiančių unikalią informaciją, kūrimo poreikis bei kombinuotas jų taikymas (Agarwal, Taffler, 2008; Jurevičienė, Bercevič, 2013 ir kt.). Remiantis atliktų mokslinių tyrimų rezultatais galima teigti, kad bankroto tikimybės prognozavimui Lietuvos įmonėse labiausiai tinkami yra logistiniai ir daugiakriteriniai logistiniai regresijos modeliai (Grigaravičius, 2003; Mileris, 2009 ir kt.). Šių modelių patikimumą akcentuoja ir užsienio mokslininkai (Pongsatat ir kt., 2004; Bellovary ir kt., 2007; Ooghe, Balcean, 2007; Ha...