数字化时代创新产业集群发展的理论与方法研究

IF 1.2 Q4 MANAGEMENT
Ganimat Safarov, Sabina Sadiqova, Milyanat Urazayeva, N. Abbasova
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引用次数: 2

摘要

本文总结了在确定不同国家创新产业集群运作的主要理论和实践原则以及数字化对其活动的形式化影响的科学辩论中的论点和反对意见。本文总结了确定创新产业集群功能的主要特征和特征的科学方法。为了证实创新产业集群绩效与数字化进程之间关系的理论背景,本文使用VOSviewer工具包对这一方向的主要Scopus出版物进行了文献计量分析。这样就有可能确定有关专题的主要的、基本的和有背景的科学研究集群,以确定其在分析期间变化的演变模式。为了确定数字化对创新与产业发展影响的实证因果关系,本文构建了创新与产业发展的综合指标。该指数考虑了工业、创业和创新发展的测量参数和区域特征。使用主成分分析和加性卷积对指标进行整合。在Stata 14.2/SE软件中,采用面板数据回归模型对数字经济对创新与产业发展综合指标的影响代理进行建模。本文还使用单因素回归模型确定了国家数字化发展的决定因素,这些决定因素在很大程度上取决于该国创新和工业发展的波动性。这项研究以10个国家为样本,包括阿塞拜疆、爱沙尼亚、格鲁吉亚、哈萨克斯坦、吉尔吉斯斯坦、拉脱维亚、立陶宛、波兰、罗马尼亚和乌克兰。该研究的时间范围涵盖2009-2021年(或可获得的最近时期)。研究结果对科学家、国家当局和地方政府都很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Theoretical and Methodological Aspects of Innovative-Industrial Cluster Development in the Era of Digitalization
This article summarizes the arguments and counterarguments within the scientific debate on the identification of the main theoretical and practical principles of the functioning of innovative-industrial clusters in different countries, as well as the formalization of the impact of digitalization on their activities. The article summarizes scientific approaches to determining the main characteristics and features of the functioning of innovation-industrial clusters. In order to substantiate the theoretical background of the relationship between innovation-industrial clusters’ performance and digitalization processes, a bibliometric analysis of the main Scopus publications in this direction is carried out using the VOSviewer toolkit. That made it possible to identify the main essential and contextual clusters of scientific research on relevant topics to characterize the evolutionary patterns of their changes during the analysis period. In order to determine the empirical causality of the impact of digitalization on innovative and industrial development, an integral indicator of innovative and industrial development is developed. The Index considers the measurement parameters and regional features of industrial, entrepreneurial, and innovative development. Indicators were integrated using the principal components analysis and additive convolution. The study modelled the influence proxies of the digital economy on the integrated indicator of innovative and industrial development using panel data regression modelling in the Stata 14.2/SE software. In the paper, it is also identified those determinants of the digital development of the state that depends to the greatest extent on the volatility of the innovative and industrial development of the country using one-factor regression models. The study is conducted for the country sample with 10 countries, including Azerbaijan, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Poland, Romania, and Ukraine. The time horizon of the study covers the period 2009-2021 (or the latest available period). The research results can be useful to scientists, state authorities, and local governments.
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