Large distributed information systems (LDIS) are the basis for digitization of production processes in industry, transport and public administration. Organization of their engineering servicing (ES) for timely restoration in case of failure is a topical issue of scientific research. LDIS consists of computer complexes which include both major and additional elements. The literature provides no solution which allows us to define the engineering servicing resources (ESR), considering the variable significance of elements of computer complexes. The task was first set and solved in this publication.
For solution of this task, we applied the mean dynamic method. This method was chosen because it makes it possible to obtain a system of differential equations for describing the change over time of the mean number of elements in different states.
Analysis of the differential equations system solution allowed us to find analytical expressions for determining ESR – the number of staff and the number of spare elements- at which the mean number of computer complexes in perfect state reaches its maximum. The results are applicable when calculating the ESR of real LDIS. They can also serve in simulation modeling as initial approximations of the optimal volume of ESR if it necessary to take into account the specific features of the system. In addition, the solution of differential equations makes it possible to solve the problem of optimizing the resources for servicing the LDIS according to economic criteria, when the costs of staff and spare elements are comparable with the income from operating the computer complexes.
The introduction of the cadastral value institute in the Russian Federation opens up new opportunities in the real estate evaluation. In this regard, the new focus for appraisers is the statistical analysis of multidimensional empirical distributions that were not previously available, because the real estate market does not have pairwise and multidimensional observations concentrated in unified databases. Data of interest to analysts is usually concentrated in different sources from different owners and belongs to different objects. The goal of combining them can be solved by comparing such data with the data of cadastral accounting, namely the cadastral number as a unique identifier of the object. Since the cadastral value corresponds to each cadastral number, it is possible to compare the cadastral value with important indicators such as the market price of the offer, the transaction price, the lease rate, the annual price indices, the capitalization rate, the discount rate, the discount on the auction and many other indicators, the formation of which involves more than two random variables. The construction of the model involves the principle of following the prices formed by pair comparisons to geometric Brownian motion, and hence the formation of logarithmically normal population. As it turned out, as a result of large-scale cadastral works carried out in the Russian Federation in 2014, the cadastral value is also subject to logarithmically normal distribution of prices (in each class of objects). For the market value (as the most probable price of the transaction in the conditions of perfect competition), this leads to functional dependencies on the cadastral value of the power type. Similarly, many other indicators will also be subject to dependencies in the form of power functions. Obviously, having a function depending on the various indicators of the cadastral value across the set of values, you can set the relationship between the various indicators, which was impossible before the introduction of the institute of cadastral value. This article proposes the method of calculation of the trade in real estate estimation based on the analysis of market statistics and databases of cadastral accounting. An analytical formula of the dependence of trade discounts from the offer price is proposed. The method allows us to set the level of the discount not only for objects included in the advertising database, but also for any object that has passed the cadastral registration.
Digital business transformation is a priority for Russian companies in all industries. To develop a company to its full value in the digital environment, it should include an IT department capable of meeting business needs. Evaluation of the current state of the IT department in terms of digital transformation will determine the company’s potential for further development. This article presents a solution to the problem of assessing the IT department’s readiness for digital business transformation by developing a quantitative assessment of the maturity level of the IT department processes for meeting the needs of the enterprise. The approach to solving this problem consists in the joint use of models for assessing the digital maturity of the enterprise as a whole and models for assessing the maturity of the IT department processes and herein is the scientific novelty of the results obtained. At the first stage of the study, based on the analysis of modern information and digital management practices, as well as on the study of approaches to assessing the digital maturity of the enterprise and the processes of the IT department, INFORMATION SYSTEMS AND TECHNOLOGIES IN BUSINESS 64 BUSINESS INFORMATICS No. 2(44) – 2018 we developed the requirements for the IT department maturity model of digital business transformation. The study identified the prospects for IT departments that affect its maturity level, developed a model for quantifying each perspective and a model for calculating the minimum level of maturity of the IT department to achieve the expected assessment of the company’s digital maturity. To assess the willingness of IT departments to digitally transform business, a regression equation of IT department maturity level is constructed from the influencing prospects (factors). The results of approbation of the model are presented.
While evaluating and selecting investment projects, modem companies are confronted with the problem of setting priorities between profitability and riskiness of these projects. Choice of a project on the basis of its profitability significantly increases risks of financial and economic activities and decreases the certainty of achieving the planned financial result. On the other hand, attempts to decrease investment projects risks may not allow one to achieve the desired profitability level. Therefore, it is vital to develop integrated multi-criteria indicators for this purpose. This article is the result of the authors’ development of an integral indicator for evaluating investment project efficiency and risks. The developed integral indicator has a matrix form. To compile the integral indicator, three groups of criteria are used: quantitative efficiency criteria, qualitative efficiency criteria and risk evaluation criteria. We propose to divide the qualitative and quantitative criteria into: 1) those defining the commercial (economic) efficiency of projects, 2) those defining their budgetary efficiency; 3) those defining their social efficiency. According to the authors, the list of criteria that define associated risks should include macroeconomic indicators and industry affiliation indicators that provide a comprehensive evaluation of the external economic situation on the corresponding market. While evaluating efficiency and riskiness of the given projects, the integral indicator developed by the authors is converted from matrix form into a quantitative indicator that is easy to interpret. The authors propose to use principal component analysis and heuristic methods (including ranking method and hierarchy analysis method) for this purpose. The results of this research can be used by companies to select investment projects.
In the paper an approach to identification of characteristics for assessment of IT strategic decisions is proposed. The main feature of the approach is associated with integration of Balanced Scorecard methodology for IT service (IT Balanced Scorecard) and COBIT standard. Such integration allows to describe a hierarchical structure of characteristics (metrics) for assessment of decisions efficiency in yje field of information technologies.
In this work the potential profitability is considered as additional criteria for classification of informational objects. It is discovered that potential profitability of the one part of information objects grows along with increase of its prevalence and drop for another part. In the article is revealed a regulatory gap of actual legislation for effective use of information objects with growing profitability along with its prevalence increase. It is offered to bridge the gap with the legal method of access encouragement for the specific class of information objects added into intellectual property law.