Liangliang Xue
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Digital transformation readiness of Kazakhstani enterprises: Mapping regional and sectoral capacities
Zaira Satpayeva, Zhanibek Bekmurat
, Tunç Medeni
, Dana Kangalakova
, Liangliang Xue
doi: http://dx.doi.org/10.21511/ppm.23(3).2025.12
Problems and Perspectives in Management Volume 23, 2025 Issue #3 pp. 161-175
Views: 264 Downloads: 131 TO CITE АНОТАЦІЯType of the article: Research Article
Abstract
Digital transformation is a key factor in the competitiveness of enterprises in the modern world. The study aims to analyze the readiness of enterprises in Kazakhstan for digital transformation at the regional and sectoral levels. The main research method was statistical analysis based on an index approach using data for 2023 from Kazakhstan’s Bureau of National Statistics, reflecting the digital readiness and digital maturity of enterprises. According to the findings, in Kazakhstan, the level of readiness of enterprises for digital transformation is heterogeneous both in regional and sectoral terms. Kazakhstani enterprises are characterized by a high level of basic digital readiness (81.4% of enterprises had computers, 79.5% – Internet access), an unsatisfactory level of advanced digital readiness (5.6% of enterprises had IT-specialists, 1.1% – own data centers, 3.1% – implemented business processes innovations in information and communication systems), and digital maturity (26.5% of enterprises had Internet resources, electronic invoices – 79.1%, automated internal business processes – 16.7%, cloud computing – 11.0%, big data technologies – 1.9%, and RFID technologies – 1.1%). A digital gap in the readiness of enterprises for digital transformation was revealed between the leading (Almaty and Astana cities, Atyrau, and Karaganda regions) and lagging (Mangystau, Turkestan, and Kyzylorda regions) regions, and between the sectors, where enterprises in industry, trade, information and communication, hospitality and healthcare are significantly ahead of enterprises in agriculture, construction, and real estate. It is advisable to make more active use of innovation infrastructure facilities to increase the digital potential of enterprises.Acknowledgments
This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (IRN 19680544 “Innovation infrastructure of Kazakhstan in the context of digitalization: assessment of the state and development of an atlas”). -
Trends of artificial intelligence-driven enterprise management development: A bibliometric analysis
Liangliang Xue, Zaira Satpayeva
, Dana Kangalakova
, Ercan Ozen
doi: http://dx.doi.org/10.21511/ppm.23(4).2025.01
Problems and Perspectives in Management Volume 23, 2025 Issue #4 pp. 1-12
Views: 66 Downloads: 8 TO CITE АНОТАЦІЯType of the article: Research Article
Abstract
Artificial intelligence (AI) has become the most eye-catching new technology in recent years, and its application is driving the transformation of enterprise management. In order to cope with the impact of new technological changes and address key issues affecting enterprise management development, it is necessary to research and clarify the basic relationship between the application of AI and the development of enterprise management. This study aims to analyze the current situation and future development direction of AI-driven enterprise management through bibliometric analysis. Scopus and Web of Science data from 2014 to July 2025 were analyzed to explore the evolutionary time, geography, and scientific landscape of this topic. The findings contribute to understanding AI’s driving role in enterprise management development. The analysis reveals exponential growth in research output on AI-driven management, accompanied by a decreasing growth rate of publications on AI-driven enterprise management since 2021. The important factors that affect research output are population and total GDP. China, the United States, and India were identified as the leading contributors, with significant research activity in this field. Keyword analysis indicates that the thematic focus is becoming more technical and universal. Thematic analysis highlights that human resource management, financial management, supply chain management, and operational decision-making are the main aspects of AI-driven enterprise management, accounting for 94% of the total number of publications. The study proposes a new direction for the development of AI-driven enterprise management, including department integration, cognitive convergence, and ethical and social responsibility.Acknowledgments
This research has been supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (IRN 19680544 “Innovation infrastructure of Kazakhstan in the context of digitalization: assessment of the state and development of an atlas”).
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