A model of a composite index of the development level digital economy of regions in various sizes is proposed. It is based on a functional network as a kind of directed graph, structured by levels based on the principles of hierarchy, modularity and balance, as well as the availability of data on the development of the digital economy. The scalar value of the required quantity was determined by means of additive convolution. The influence of the subjective factor was excluded by moving away from the expert determination of weighing measures of particular indicators (which are included in the composite index) and using a calculation based on the standard deviation. The proposed approach was tested in the framework of identifying the differentiation of the development level digital economy of regions in Russia, as well as comparing European and Russian practices.

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The purpose of this article is to analyze the most popular maturity models in order to identify their strengths and weaknesses. Research conducted by international project management communities such as Software Engineering Institute (SEI), Project Management Institute (PMI), International Project Management Association (IPMA), Office of Government Commerce (OGC) and International Organization for Standardization (ISO) showed that organizations with high managerial maturity are more likely to achieve their planned project goals than those that do not identify and standardize their best management practices. This circumstance has encouraged scientists from all over the world to start developing various models that can measure and evaluate managerial maturity in projects. Nowadays, the variety of models created has led to considerable difficulty in understanding the strengths and weaknesses of each model. To solve this problem, the article authors conducted a critical analysis to identify the strengths and weaknesses of the most popular project management maturity models. The results obtained will be of interest to project managers, members of project teams, heads of organizations, project offices and everyone involved in the development of project activities. Based on the analysis, it was found that the most developed maturity models are based on international codes of knowledge of project management. Most maturity models ignore the presence of structural and infrastructural elements, such as a workplace, the necessary equipment and software, the availability of professional standards, instructions, regulations, etc. It was also revealed that there are no processes for assessing the effectiveness and efficiency of using the best practices in the maturity models.

This article raises the issue of decision support system (DSS) development in enterprises concerning the compensation system (CS). The topic is relevant as the CS is one of the main components in human resource management in business. A key element of such DSSs is CS models that provide predictive analytics. Such models are able to give information about how a particular CS affects output, product quality, employee satisfaction, and wage fund. Thus, the main goal of this article is to obtain a CS statistical model and its formulas for determining the probability densities of resultant indicators. To achieve this goal, the authors conducted several blocks of research. Firstly, mathematical formalization of CS functionality was described. Secondly, a statistical model of CS was built. Thirdly, calculations of CS result indicators were made. Reliable scientific methods were used: black box modeling and statistical modeling. This article proposes a statistical and analytical model. As an example, a piecework-bonus system statistical model is demonstrated. The discussion derives formulas of integral estimations showing the probability density of the resulting CS indicators and the related statistical characteristics. These results can be used to predict the behavior of the workforce. This constitutes the scientific novelty of the study, which will establish significant advances in the development of DSSs in the field of labor economics and HR management.

This report is a written tabular compilation of the significant metalliferous and selected non-metalliferous lode deposits and placer districts of the Russian Far East, Alaska, and the Canadian Cordillera. The report provides detailed summaries of the important features of the significant lode deposits and placer districts along with a summary of mineral deposit models, and a bibliography of cited references. Data are provided for 1,079 significant lode deposits and 158 significant placer districts of the region. This version of the report is issued on standard paper