Digital transformation readiness of Kazakhstani enterprises: Mapping regional and sectoral capacities

Technological changes that come with industrial revolution have largely affected businesses, as well as society. With the current technological shift and Fourth Industrial Revolution, many questions arise regarding the impacts and effects on current ways businesses operate. This study presents a retrospective analysis and overview of previous industrial revolutions. The aim of the retrospective analysis is to identify common characteristics that may lead to lessons learned for the forthcoming Fourth Industrial Revolution and thus complement the current debate on technological change. All previous industrial revolutions have led to change in business environments and new challenges for managers and owners. The findings show that all previous revolutions have led to increase in the number of service jobs created. The key approach of successful countries during the times of industrial revolution has included education as the source of new skills and knowledge necessary for adaption. Countries that were able to produce high skilled people could not only invent, but also adapt to new technologies sooner than others. Similarly, these approaches included introduction of new managerial practices in order to be able to utilize new technologies and new skilled workers effectively. The research article processes secondary data together with literature review on this topic.

In the current era, the challenges faced by SMEs in Indonesia are becoming increasingly complex. Previously, the primary challenge for SMEs has been to enhance performance. However, with the emergence of information technology, SMEs are now required to compete fiercely. SMEs in Indonesia are still in the process of digital transformation to improve their business strategies, thus limiting research focused on digital transformation in SMEs. Research also considers market complexity and digital strategy as crucial factors for SMEs. The aim of this study is to analyze the role of digital transformation in influencing SME performance. The research approach is quantitative, involving 171 SMEs owners as respondents. The instrument utilized is a Likert scale questionnaire, focusing on the majority of SMEs in Indonesia, particularly those in Java, the most populous island and business center of the country. This includes SMEs operating within various sectors, such as culinary, fashion, retail, and creative industries. The results indicate that digital strategy and market complexity influence digital transformation and SMEs performance. The research findings suggest that digital transformation mediates the influence of digital strategy and market complexity on SME performance. The novelty of this study lies in its focus on the current SMEs digitalization strategy area. This study indicates that digital transformation is an essential aspect affecting current SME performance. The results suggest that SMEs require focused strategies to strengthen resources and gain competitive advantage in complex markets.

The paper deals with the assessment of the socio-economic development of Ukrainian regions using Data Science methods and multidimensional analysis, including taxonomy, n-dimensional classification, and ensemble decision trees methods. The methodological bases of economic regions devel¬opment by the economic and mathematical modeling methods were investigated. The necessity of improving and further developing estimation models of the regional economic development using business analytics tools and multidimensional scaling methods was investigated.
The ensemble decision trees methods was applied for the classification model of economic development of the Ukrainian regions according to the conceptual base of the research on regional econom¬ic development. It will increase the quality level of administrative decisions making on regional de¬velopment asymmetry equalization. It is determined that in Ukraine, there is a significant imbalance of regions clusters with high and low economic level. Here was investigated the relationship between the two groups of economic development indicators – the indicators of the economic development regional performance and the group of economic potential. The results of the classification model allow identifying the set of indicators that have significant impact on the overall economic development. The developed ensemble model allows carrying out qualitative recognition and prediction of the state probability of economic development. It will improve the quality of decision making pro¬cesses on equalization of regional development asymmetry.
The further research gives the possibility to develop the system of levers directions of regional development imbalance equalization, to determine priority vectors of sustainable development of both the regions and the country.