Paper
2 May 2023 Bibliometric analysis of the research hotspots and trends in diversification strategy
Yuxin Fu, Shikui Cao
Author Affiliations +
Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 126422H (2023) https://doi.org/10.1117/12.2674772
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China
Abstract
In order to clarify the relevant elements, stage characteristics, evolutionary context and frontier trends of diversification strategy research, and further guide enterprises to explore diversification strategies, the bibliometric method was used, and the literature elements including keywords were analysed by COOC13.4, VOSviewer1.6.13 and other software. Combined with existing papers, the visualized knowledge graph was drawing, and the hotspots and trends were analysed. The research content of diversification strategy presents the characteristics of multi-dimensional and staged. Scholars have conducted research on the motivation and influencing factors from multiple dimensions such as the internal and external environments of enterprises, the classification of diversification strategies, and the classification of different industries. Through visual analysis, the research process of the diversification strategy in the past 20 years was divided into the following three stages, namely "research boom", "gradual saturation" and "rich development". The main trend of future diversification strategy research is that, combining personalized internal environment and changing external environment, constantly enriching its influence way.
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Yuxin Fu and Shikui Cao "Bibliometric analysis of the research hotspots and trends in diversification strategy", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 126422H (2 May 2023); https://doi.org/10.1117/12.2674772
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KEYWORDS
Analytical research

Industry

Visual analytics

Visualization

Document management

Statistical analysis

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