This manuscript aims to present possibilities for developing mobile and smart platforms and systems in teaching and learning the English language for engineering professionals in different engineering study programs. Foreign language teaching and learning processes are based on traditional methods, while in engineering and technical sciences, teaching and learning processes include different digital platforms. Therefore, the following hypotheses were stated. (H₁) It is possible to develop a software solution for mobile platforms that can have a higher level of interactivity, and it may lead to better learning outcomes, especially in the field of adopting engineering vocabulary. (H₂) Implementation of the developed solution increases motivation for learning and leads to a higher level of satisfaction with the learning process as a part of the quality of life. (H₃) Students who have digital and mobile platforms in the learning process could have higher achievement values. This manuscript presents software application development and its implementation in teaching English as a foreign language for engineering and technical study programs on the bachelor level. Initial results in implementation and satisfaction of end users point to the justification of implementing such solutions.

In order to adapt to ever-changing customer needs and satisfy them, good Business Process Management (BPM) in Small and Medium-sized Enterprises (SMEs) is crucial. The target group of this research is production SMEs whose BPM can be monitored respecting the values of key performance indicators (KPIs). This paper shows how improving the performance of the observed business processes can improve the level of customer satisfaction. This improvement should lead to the sustainability of SMEs in the market. In this paper, evaluation of business processes performance is defined as a multi-criteria decision problem. The relative importance of considered KPIs and their imprecise values are described by linguistic expressions, which are then modeled by triangular intuitionistic fuzzy numbers (TIFNs). Calculation of KPI weights is done by using the fuzzy analytic hierarchy process (FAHP). Evaluation of BPM success is conducted respecting the obtained KPI weights and KPI values. An optimal solution for BPM success improvement, respecting customer satisfaction indicators, is calculated using the Artificial Neural Network (ANN) and Genetic Algorithm (GA) approaches. By applying the proposed model, managers of production SMEs can determine the management initiatives that will improve their business and the sustainability of their companies.

This article presents the methodology and tools for the econometric analysis and assessment of the innovation development of the Russian Arctic regions, under the Triple Helix concept. The econometric calculations based on this methodology allow the express assessment of innovation development of a region and the contribution of the science and education complex (SEdC), industries, and the government, to the integral index of innovation development of this region, using minimum key statistical indicators in the field of science and innovation. The calculation results obtained using the author’s methodology show the adequacy of the express rating, with respect to the rating data obtained using other methodologies. The main advantage of the proposed methodology is the elimination of the human factors arising from the weighing coefficients and the results of the expert assessments used in the other rating methodologies. The calculation results obtained using this methodology might be useful to the executive bodies of state authorities, business entities, and scientific and educational institutions, for an express assessment and for making various organizational and managerial decisions on innovation development in a region.