This paper empirically investigates the effects of transport infrastructure on economic growth in Central and Eastern European Member States (C.E.M.S.) in the period 1995–2016. During the transition period in C.E.M.S., most investments were focused on the roads, while railways have been lagging for decades. The aim of this paper is to estimate the effects of transport infrastructure (road and rail) on economic growth while controlling with other variables such as population growth, gross fixed capital formation and trade openness. We use panel data analysis with three standard estimators: pooled ordinary least squares, fixed effects and random effects. The results show positive effects in case of all estimated variables, except the railway infrastructure where the effects seem to be negative. The results illustrate the long-standing problem of inefficient and outdated railway infrastructure. These results should be seen in a broader context, especially in the light of the ongoing desire to reduce CO₂ emissions that are to a large extent produced by road transport, while railway transport is more environmentally friendly. This paper supports the European Union’s guidelines for the need to invest in railway infrastructure to ensure effective transport in the long term, create competitive advantages, reduce greenhouse gas emissions and thus simulate sustainable economic growth in C.E.M.S.

Even though trade tariffs have generally fallen since the GATT agreement, non-tariff trade barriers still exist and show an upward trend. An important type of non-tariff trade barrier is logistics service related to the transport of goods to foreign markets. Efficient logistics is of great importance for small and open economies such as the Central and Eastern European EU member countries that became EU members in 2004 or later and are in the process of economic convergence with the old EU member countries, mostly through trade. On the other hand, logistics is important for old EU member countries because it influences competitiveness in global supply chains. The aim of this paper is to examine the homogeneity of the two blocks of EU countries in terms of logistics performance, i.e. to examine the impact of logistics performance on the international bilateral trade of the EU15 and CEMS with the rest of the world in the period 2010–2018. We develop and estimate a structural gravity model with Poisson pseudo-maximum probability estimator, using the LPI and its sub-indices as the main independent variables of interest. Our results show that differences in LPI values have heterogenous impact on bilateral trade, especially when considering trade in different classes of goods and different groups of country pairs.

Logistics has become one of the most important economic sectors. It significantly affects the transport infrastructure and many other sectors that are crucial for the country’s development. It is the factor that also influences trade efficiency. However, the question arises if logistics performance is significant for the trade of critical goods which are energy raw products. The aim of the paper is primarily to investigate the EU energy trade flows in general and to estimate the effect of logistics performance on the international trade of energy raw products. The energy raw products are grouped into solid, liquid, and gaseous products, and separate estimates are made for their export and import. The analysis also differentiates between the trade flows, that is export and import within the EU and trade flows between EU member states and third countries. The empirical model is based on the theory of gravity model extended to include the six subcomponents of the Logistics Performance Index (LPI). The results present that: (1) the standard gravity model variables, such as GDPs of reporter and partner countries and contiguity, are successful in explaining the trade flows of solid and liquid raw energy but in case of gas products, are insignificant; (2) the results indicate that all logistics’ performance subcomponents are highly significant and show positive effects on the export of liquid energy products, while for the solid and gas products, it seems to be insignificant when the energy commodities are more complex and costly to transport and store, and therefore, contiguity, i.e., when countries share a common border, positively affects energy trade; (3) the EU imports most liquid energy products, but is generally very dependent on energy imports. EU policymakers should strive to either make more use of domestic resources or switch more to renewable energy sources.

The purpose of this paper is to understand the concept of a fourth-party logistics provider and to identify his functions and importance for an organization. Although the concept of fourth-party logistics provider is present in academic researches for a relatively long time, it still remains underestimated. The paper presents a conceptual model that is based on the research of fourth-party logistics provider within the exsisting theorethical and empirical literature. The results have shown that fourth-party logistics provider is not incorporated enough into contemporary supply chain solutions, although a growing demand for it is evident. Future research may be broadened by implementing both qualitative and quantitative approach to evaluate the impact of fourth-party logistics provider on a business performance distinguishing among industries. This paper provides a knowledge-based conceptual framework to understand the value of fourth-party logistics provider inclusion in an organisation supply chain.

The aim of this paper is to assess the role of hard and soft infrastructure in trade, distinguishing between traditional trade and supply-chain trade. Using factor analysis, we construct four aggregate trade facilitation indicators where we measure hard infrastructure as physical and ICT infrastructure, while soft infrastructure accounts for border efficiency and institutional efficiency. For traditional trade, we use bilateral trade data from UN Comtrade. Supply-chain trade is measured in terms of domestic value-added (DVAFX) embodied in foreign gross exports and foreign value-added (FVA) embodied in domestic gross exports obtained from Eora MRIO database. We use panel data regression analysis with an empirical model specification based on a gravity model and covering the 2000–2019 period. We estimate model with the Poisson Pseudo-Maximum Likelihood Estimator (PPML). To control multilateral trade-resistance terms (MRT), we included reporter and partner fixed effects along with country pair fixed effects. The results confirm a statistically significant relationship between hard and soft infrastructure and trade. ICT and border efficiency have the strongest impact on both types of trade. Supply-chain trade responds most intensely to improvements in institutional efficiency. Results imply that ICT infrastructure and border efficiency might hold even greater importance for CEMS’s traditional and supply-chain trade.