Business Management

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  FORECASTING THE EFFECTIVENESS OF NON-STATE PENSION FUND INVESTMENT STRATEGIES: THE CASE OF GEORGIA

  This paper evaluates the effectiveness of Georgia’s non-state pension fund using monthly data for 2022–2023 and develops short-to-medium-term forecasts to 2030. We assemble indicators on pension contributions, investment returns, and the exchange rate, and define a fund-effectiveness measure to capture the system’s ability to meet obligations. ... This paper evaluates the effectiveness of Georgia’s non-state pension fund using monthly data for 2022–2023 and develops short-to-medium-term forecasts to 2030. We assemble indicators on pension contributions, investment returns, and the exchange rate, and define a fund-effectiveness measure to capture the system’s ability to meet obligations. Ordinary Least Squares (OLS) regression is used to estimate the relationship between effectiveness and its determinants; we verify time-series properties with Augmented Dickey–Fuller tests, assess Granger causality, and construct an ARIMA model to forecast dynamics under current policies. The results indicate a positive and statistically significant association between contribution inflows and effectiveness, while the link between investment returns and effectiveness is weak or negative during the sample period, consistent with portfolio transition, limited diversification, and market volatility. Exchange-rate movements appear positively associated with effectiveness, reflecting the valuation of foreign assets, but also imply additional risk to beneficiaries’ purchasing power. Forecasts suggest that, absent reforms, effectiveness is unlikely to rise materially by 2030. We discuss implications for policy design and governance. Priority actions include: strengthening risk management and diversification; aligning asset duration with liabilities; instituting foreign exchange risk hedging where appropriate; publishing clearer performance and risk disclosures; and enhancing default portfolio design and member choice architecture. The findings inform the calibration of contribution policy and investment guidelines for Georgia’s non-state pension system.

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  CHALLENGES AND SOLUTIONS FOR SUSTAINABLE TRANSPORT IN THE ERA OF NEW ENVIRONMENTAL REQUIREMENTS IN BULGARIA AND TÜRKIYE

  The background of the research is based upon the conclusions of the International Transport Forum (OECD, 2-21) that one of the big challenges for the environment comes from the transportation sector, which is responsible for approximately 23% of the discharged CO2 emissions; this quantity is expected to increase to 40% by 2030 and to 60% by 2050. ... The background of the research is based upon the conclusions of the International Transport Forum (OECD, 2-21) that one of the big challenges for the environment comes from the transportation sector, which is responsible for approximately 23% of the discharged CO2 emissions; this quantity is expected to increase to 40% by 2030 and to 60% by 2050. The already expressed negative tendency is calling for new models for freight transport represented in the form of inter-modality. This means the logistics side of international economic relations, represented by land mode of transport (road and rail), inland waterways, short-sea shipping, and even airborne transport at short distances, should make use of viable combinations to decrease the harmful substances; it also concerns domestic transport policy which should stimulate non-road transportation solutions. The European Green Deal practically outlines the plan for the decarbonization of the economies of the member states of the union until 2050, with the aim of improving the well-being and health of European citizens and future generations with an accent over transport activities. Usually, logistics providers offer transport solutions, combining several modes, led by stakeholders’ expectations for reduced time and costs of transferring goods, reliability, and frequency of services. The biggest challenge is to design a resilient transport network, where the users can easily switch between transport modes in real time, while there is enough evidence that combined transport solutions are in accordance with the contemporary requirements towards freight transport. Infrastructure investments, easing transborder connections and interoperability in general have a positive effect over the development of combined transport. This paper is addressing the opportunities and difficulties in employing combined transport solutions using the methodology SWOT-TOWS and applying the research results to the existing possibilities in Bulgaria and Turkey as a neighbor non-EU country in the role of advanced competitor in the development of combined transport solutions. The conclusions confirm that economic development and its interaction and dependence on international logistics development is the most important factor of the environment encouraging or detaining the combined transport solutions. It also affects investments in transport infrastructure, the application of ITS and AI, the technological factors influencing the general trends of transport development and in particular, freight transport.

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  CLUSTER ANALYSIS OF E-COMMERCE IN THE EUROPEAN UNION COUNTRIES

  E-commerce is the fastest growing segment in the trade sector and is of ever-increasing importance to the economy of the European Union. However, huge imbalances occur between individual countries when measuring the intensity of this type of trade. In the context of the new realities, the aim of the present study is, based on cluster analysis, to ... E-commerce is the fastest growing segment in the trade sector and is of ever-increasing importance to the economy of the European Union. However, huge imbalances occur between individual countries when measuring the intensity of this type of trade. In the context of the new realities, the aim of the present study is, based on cluster analysis, to segment and identify the differences between the EU Member States in the field of e-commerce, and on this basis to formulate corresponding conclusions. Cluster analysis is applied to selected indicators (I) for measuring e-commerce in the European countries—I1. “E-commerce sales of enterprises”; I2. “Value of e-commerce sales”; I3. “Internet purchases by individuals”. The clustering of the studied data refer to 2024. Technical processing and calculations are made using IBM SPSS Statistics. As a result of the study conducted, the 27 Member States are differentiated into four homogeneous clusters, which allows them to be interpreted as: leading countries in the e-commerce segment; countries catching up with the leaders; countries moderately advancing in e-commerce; countries in an unenviably lagging position.