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Atsižvelgiant į darbo rinkos raidos netolygumus, siekiama įvertinti bendrųjų nedarbo rodiklių raidos tendencijas Lietuvoje. Esminis šiame darbe išskirtų gyventojų grupių situacijos darbo rinkoje diferenciacijos požymis – amžius. tačiau prioritetas čia teikiamas jaunimui. Kitas ryškus tyrimo prioritetas – nedarbas, nors plačiau analizuoti ir aktyvumo bei užimtumo rodikliai. Siekiant užtikrinti tyrime atliktos stebėsenos sistemiškumą, atlikta Valstybės duomenų agentūros (Lietuvos statistikos departamento) ir Užimtumo tarnybos nedarbo rodiklių lyginamoji analizė. Vertinant nedarbo (bedarbių skaičiaus) pokyčius, išskirtos paskiros jiems poveikį darančios veiksnių grupės. Vertinimo sistemiškumas užtikrinamas ir lyginant priešingas raidos kryptis išreiškiančių darbo rinkos rodiklių santykinius dydžius (užimtumo ir nedarbo), suteikiant jiems tiesioginę lyginamąją raišką. Maksimalus tyrime naudojamas laiko intervalas apima 1998–2021 m. laikotarpio statistinius ir administracinius duomenis. Kita vertus, siekiant ypač akcentuoti ankstesnės pandemijos poveikį, stebimų pasikeitimų tendencijų specifiką ir atsižvelgiant į duomenų disponavimo galimybes, straipsnyje išryškinami ir trumpalaikiai pokyčiai (iki 2022 m.), kurie apima 2–6 metų laikotarpį.

In modern economy information and communication technologies (ICT) play the essential role. The improvement of ICT infrastructure, developing ICT knowledge and usage can lead to economic growth due to higher productivity. However, this impact can depend on countries’ ICT investment or expenditure amount, reached ICT development and productivity levels. Moreover, ICT impact on productivity growth can occur after a certain period. Consequently, forming the ICT development strategies it is important to identify ICT impact period and impact differences between relatively high and low productivity countries. Authors examined the impact of ICT investments on productivity in EU countries covering the period of 1995–2015. Research results have revealed that ICT development positively and directly influences productivity, but this effect manifests with a lag in time. Moreover, it was found that the impact of ICT development on productivity is about twice bigger in countries with relatively high productivity level compared with countries that have relatively low productivity level.

Suppose that f is the characteristic function of a probability measure on the real line R. In this paper, we deal with the following problem posed by N.G. Ushakov: Is it true that f is never determined by its imaginary part f ? In other words, is it true that for any characteristic function f there exists a characteristic function g such that f ≡ g but f ≡ g?We study this question in the more general case of the characteristic function defined on an arbitrary locally compact abelian group. A characterization of what characteristic functions are uniquely determined by their imaginary parts are given. As a consequence of this characterization, we obtain that several frequently used characteristic functions on the classical locally compact abelian groups are uniquely determined by their imaginary parts.

Understanding customer loyalty has been a growing concern for the services industry. In a context of increasing competitive pressures, such loyalty is seen as a key element in service companies’ success. Maintaining customer loyalty and identifying its underlying factors, however, are recognizably difficult to do. Grounded on the use of cognitive mapping techniques, this paper proposes a knowledge-based framework for the identification of the key determinants of customer loyalty, and the relationships among them. A step-by-step guide to the development of such a framework is presented, and illustrated through a practical application in the banking context. The resulting findings are supportive of the applicability of such methods for understanding customer loyalty, and the improvement of long-term relationships with customers. They are furthermore indicative of new ways in which knowledge can be incorporated into management activities to improve service outcomes. Some managerial implications of our contribution and avenues for future research are also reported.

Nowadays environmental performance of suppliers becomes more important because of competitive conditions. Besides, the economic performance has been a significant factor for companies to choose their suppliers. In this paper, a new integrated model is proposed for supplier evaluation and order allocation which considers both environmental and economic factors. We use the EDAS (Evaluation based on Distance from Average Solution) method and interval type-2 fuzzy sets for evaluation of suppliers with respect to environmental criteria. According to this evaluation two parameters are defined for each supplier: positive score and negative score. These parameters, together with cost parameters, are utilized to propose a multi-objective mathematical model for determination of order quantity from each supplier. A numerical example is used in this paper to show the applicability of the proposed integrated model. Also, a sensitivity analysis is made to examine the effect of weighting environmental criteria on total purchasing cost and quantity of order from each supplier. The results show that the proposed model is efficient and applicable for real-world problems.

Mass appraisal, or the automatic valuation of a large number of real estate assets, has attracted the attention of many researchers, who have mainly approached this issue employing traditional econometric models such as Ordinary Least Squares (OLS). However, this method does not consider the hierarchical structure of the data and therefore assumes the unrealistic hypothesis of the independence of the individuals in the sample. This paper proposes the use of the Hierarchical Linear Model (HLM) to overcome this limitation. The HLM also gives valuable information on the percentage of the variance error caused by each level in the hierarchical model. In this study HLM was applied to a large dataset of 2,149 apartments, which included 17 variables belonging to two hierarchical levels: apartment and neighbourhood. The model obtained high goodness of fit and all the estimated variances of the parameters in HLM were lower than those calculated by OLS. It can be concluded as well that no further neighbourhood variables need be added to the model to improve the goodness of fit, since almost all the residual variance can be attributed to the first hierarchical level of the model, the apartment level.

It is the intention of the European Union to create a growing and sustainable European economy by 2020, a much more moderate target than the 2010 target of becoming the most competitive and dynamic knowledge-based economy in the world. This intention has to be supported by an adequate Optimization and Decision Support System. Therefore, MULTIMOORA is proposed. MULTIMOORA is a quantitative method, which compares multiple and optimum objectives, expressed in different units, as much as possible on a nonsubjective basis. In opposition to similar methods MULTIMOORA does not need normalization, being based on dimensionless measures. Importance of an objective can eventually be given by the stakeholders concerned. MULTIMOORA is composed of three approaches: Ratio System, Reference Point and Multiplicative Form Methods, all of the same importance and each controlling each other. Twenty two objectives, 10 originating from statistics and 12 from statistics and forecasts, important for the future, characterize the 27 EU-Countries economies as a preparation for 2020. Which of these countries are the best prepared for 2020? A Dominance Theory, summarizing the three obtained ordinal numbers per country, ranks the 27 countries for that purpose.

Extension of optimization to decision-making systems is challenging topic of research. This paper surveys the special journal issue on the subject “Optimization and intelligent decisions.” Papers on intelligent decision theory as well as on decision in economic systems are presented and discussed. Information technologies for web-based intelligent systems environment, which offers generic, modular, flexible and scalable system solutions for information retrieval, extraction, fusion, knowledge discovery and intelligent decision support, might be a subject of future research extending optimization in decision-making.

Implementation of sustainable development policy is one of the most complicated tasks and challenges faced by the global community. The efforts to move the concept of sustainable development from a theoretical level to a decision-making level and to link the economic development to environment are followed by a number of problems. Several theories and individual methods of the development of trends exist and they could be applied in the forecast of potential future. The setting of concerned social problems, related to scientific knowledge, its receipt and representation, consists of 4 different but inter-related elements: real world, data, theory, model. Analysis of the sustainable development must be based on a systematic approach. The paper describes the methodology for the creation of future insights, the principles of application of the expert method, the types of future scenarios, and their application in drafting the general plan of the territory of Molėtai district. It provides a comparison of the offered scenarios for the future of Molėtai. Conclusions and recommendations finalize the article.

A simultaneous perturbation stochastic approximation (SPSA) method has been developed in this paper, using the operators of perturbation with the Lipschitz density function. This model enables us to use the approximation of the objective function by twice differentiable functions and to present their gradients by volume integrals. The calculus of the stochastic gradient by means of this presentation and likelihood ratios method is proposed, that can be applied to create SPSA algorithms for a wide class of perturbation densities. The convergence of the SPSA algorithms is proved for Lipschitz objective functions under quite general conditions. The rate of convergence [...] of the developed algorithms has been established for functions with a sharp minimum, as well as the dependence of the rate of convergence is explored theoretically as well as by computer simulation. The applicability of the presented algorithm is demonstrated by applying it to minimization of the mean absolute pricing error for the calibration of the Heston stochastic volatility model.