The purpose of the work is to study the mechanisms used to ensure the sustainable development of the company based on the strategic competitive advantages of postal companies. The research uses: methodology based on the application of general scientific methods to ensure the sustainable development of the company and strategic management methods for the development of strategic competitive advantages; statistical methods for analyzing the state and development of the company and methods of expert assessments to determine the prospects for the development of the company, to identify the strategic competitive advantages applied in practice. The originality of the research lies in the fact that the proposed methodology and algorithm for the formation of a sustainable development mechanism allow for the sustainable development of the company under study. The identified and described basic components of the mechanism for the sustainable development of postal companies make it possible to analyze effectively, evaluate and implement the principles of their sustainable development. A scheme for compiling a list of tasks to ensure the sustainable development of the company and methods of forming a mechanism for sustainable development of the company based on the design of managerial innovations and benchmarking have been created.
The following paper explores the development of a statistically based index evaluating digitalization processes to assess the digital divide between the regions of Kazakhstan: resource-based (oil and gas) regions and regions where the service sector dominates the GRP. As a method for forming such an indicator, the authors suggest using factor analysis, which reduces the dimension of factors while maintaining the reasoning behind a significant part of the data variability. This approach is preferable because the index is formed on the basis of statistically objective estimates rather than that of subjective expert opinion. The results of the factor analysis were interpreted as the following two qualitatively different subindices that formed the final Economy and Society Digitalization Index, namely, for resource-based (oil and gas) regions: subindex of digital consumption by households and subindex of digital consumption by organizations; for service-dominated regions: subindex of digital consumption by households and organizations, and subindex of digitalization of labor management processes. The combined values of the calculated subindices allowed us to conclude that the introduction of information and communication technologies into the consumer environment is greater than into the activities of economic entities. Open innovations are revealed to create additional opportunities for obtaining new knowledge and additional tools and ideas that can lead to bridging the digital divide in the regions of Kazakhstan. The analysis of descriptive statistics of these values allowed us to draw a number of conclusions available that can be used to form regional digital policy. First, the regional population shows a fairly homogeneous high level of consumption of telecommunications services, which indicates their availability. Second, the majority of economic entities throughout the country have successfully passed the first stage of digitalization, which consists in the use of Internet technologies; although, not all of them are characterized by a trend toward the digitalization of business processes. Thirdly, for most organizations, the digital development of human capital still remains an important task. Further statistical research of regional differentiation of the values of the proposed digital development indicator will allow a deeper understanding of the reasons for the digital divide in Kazakhstan.
In the age of technology, the role of innovation is increasing, the development of which depends on financial investments, which indicates a close relationship between investment and innovation. In this regard, the authors conducted a correlation and regression analysis, which helped to determine the factors influencing innovation activity on the example of the regions of Kazakhstan. As a result of modeling, a high degree of influence on innovation activity was determined by factors such as investment in innovation, as well as the number of created and used innovation facilities. The regression model was tested on the indicators of Almaty, which made it possible to make predictions.
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