Work

The Spatiotemporal Distribution Characteristics and Influencing Factors of Unicorn Companies and Gazelle Companies in Jiangsu Province

Year: 2024

Type: article

Abstract: In recent years, Jiangsu Province has increasingly prioritized the coordinated regional development of innovation. Unicorn and gazelle companies, characterized by technological or business model innovation, serve as significant indicators of regional innovation capacity. Therefore, this study uses unicorn and gazelle companies recognized between 2020 and 2022 in Jiangsu Province as samples, employing ArcGIS and geographical detectors to investigate the spatial distribution characteristics and influencing factors of these companies, and to propose optimization strategies, with the aim of assessing the innovation landscape of Jiangsu Province. The key findings and conclusions are as follows: (1) over the past three years, the average nearest-neighbor distance decreased from 10.491 km to 1.706 km, indicating a significant spatial agglomeration; the peak core density of business clusters increased substantially, reflecting the growth in the number of companies as clustering deepened. (2) Unicorns and gazelles exhibit clear clustering characteristics. The standard deviation ellipse of unicorns is centered around Suzhou, while gazelles display a continuous distribution pattern in Southern and Central Jiangsu. (3) Geographical detector analysis reveals that the level of urban technological innovation is the most influential factor, with key determinants of distribution including total retail sales and patent grants. (4) To foster the development of unicorn and gazelle companies in Jiangsu, the government should focus on enhancing regional innovation capacity, ensuring the sustainable nurturing of innovative firms, and promoting the catalytic development of surrounding areas through core cities.

Source: Sustainability

DOI: 10.3390/su162411281

Authors: Xueyu Li, Lei Ye, Huangwei Chen

Institution: Nantong University

Language: English

Topic: Regional Economics and Spatial Analysis

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,728