Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, China
In response to Boschma’s concern that the implications of relatedness- and unrelatedness-based diversification strategies lack empirical evidence at disaggregated levels and in the context of the Global South, this study generates a unique dataset at the city level and explores how these smart speci...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/12/2/62 |
| _version_ | 1797296950573268992 |
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| author | Zhen Yue Meisha Zhang Shuran Yang Kai Zhao |
| author_facet | Zhen Yue Meisha Zhang Shuran Yang Kai Zhao |
| author_sort | Zhen Yue |
| collection | DOAJ |
| description | In response to Boschma’s concern that the implications of relatedness- and unrelatedness-based diversification strategies lack empirical evidence at disaggregated levels and in the context of the Global South, this study generates a unique dataset at the city level and explores how these smart specialization strategies (S3) may explain digital industry innovations within a specific regional innovation system, i.e., the Yangtze River Delta, China. The findings reveal that both relatedness density and knowledge complexity play a positive role in explaining digital industry innovations. However, the relationship between relatedness and knowledge complexity and its interactive effects on innovation performance are less straightforward. In our study, we found that efficient cooperation between relatedness and complexity can only be achieved if the level of government intervention is moderate. Therefore, the discussion of S3 focuses on more than the dichotomous argument between relatedness and unrelatedness. Many socio-economic factors also impact the effectiveness of these theoretical components within different innovation systems, which are largely overlooked by present studies. |
| first_indexed | 2024-03-07T22:12:16Z |
| format | Article |
| id | doaj.art-95c5f596624a469b87ecf84d43743961 |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-07T22:12:16Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-95c5f596624a469b87ecf84d437439612024-02-23T15:36:12ZengMDPI AGSystems2079-89542024-02-011226210.3390/systems12020062Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, ChinaZhen Yue0Meisha Zhang1Shuran Yang2Kai Zhao3School of Foreign Studies, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Marxism, Changan University, Xi’an 710064, ChinaSchool of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, ChinaSoft Science Research Base of Shaanxi High-Quality Economic Development, Xi’an Jiatong University, Xi’an 710061, ChinaIn response to Boschma’s concern that the implications of relatedness- and unrelatedness-based diversification strategies lack empirical evidence at disaggregated levels and in the context of the Global South, this study generates a unique dataset at the city level and explores how these smart specialization strategies (S3) may explain digital industry innovations within a specific regional innovation system, i.e., the Yangtze River Delta, China. The findings reveal that both relatedness density and knowledge complexity play a positive role in explaining digital industry innovations. However, the relationship between relatedness and knowledge complexity and its interactive effects on innovation performance are less straightforward. In our study, we found that efficient cooperation between relatedness and complexity can only be achieved if the level of government intervention is moderate. Therefore, the discussion of S3 focuses on more than the dichotomous argument between relatedness and unrelatedness. Many socio-economic factors also impact the effectiveness of these theoretical components within different innovation systems, which are largely overlooked by present studies.https://www.mdpi.com/2079-8954/12/2/62smart specializationrelatednessknowledge complexityinnovation systemYangtze River Deltadigital industry |
| spellingShingle | Zhen Yue Meisha Zhang Shuran Yang Kai Zhao Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, China Systems smart specialization relatedness knowledge complexity innovation system Yangtze River Delta digital industry |
| title | Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, China |
| title_full | Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, China |
| title_fullStr | Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, China |
| title_full_unstemmed | Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, China |
| title_short | Understanding the Role of Smart Specialization Strategies (S3) within a Regional Innovation System: Evidence from Digital Industries in the Yangtze River Delta, China |
| title_sort | understanding the role of smart specialization strategies s3 within a regional innovation system evidence from digital industries in the yangtze river delta china |
| topic | smart specialization relatedness knowledge complexity innovation system Yangtze River Delta digital industry |
| url | https://www.mdpi.com/2079-8954/12/2/62 |
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