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Abstract
Over the past decades, the development of knowledge-based and innovation-led economy has gained the attention of higher education (HE) institutions. The Quadruple Helix Model of the relations amongst universities, industries, government and society provides a general framework for systematically investigating the dynamics of innovation amongst these agents. However, knowledge about their influence on cross-boundary cities is limited. The ways in which HE institutions bridge different innovation systems also remain unknown. This study thus examines the innovation systems of two neighbouring cities along the border, namely, Hong Kong and Shenzhen, and their multidirectional innovation cooperation. Research findings suggest that the two innovation systems differ in terms of the unequal role of the agents. The systems seem mutually complementary in terms of HE capacity and industrial composition, and cross-boundary cooperation in HE sectors currently occurs through various means. This study sheds light on the development of and cooperation between cross-border innovation systems.
| Original language | English |
|---|---|
| Pages (from-to) | 213-229 |
| Number of pages | 17 |
| Journal | Journal of Higher Education Policy and Management |
| Volume | 42 |
| Issue number | 2 |
| Early online date | 10 Dec 2019 |
| DOIs | |
| Publication status | Published - Apr 2020 |
Funding
The role of universities in knowledge creation and diffusion has been well recognised in previous studies (Etzkowitz et al., 2000). However, the Quadruple Helix Model emphasises that the innovation ecosystem encompasses ‘mutually complementary and reinforcing innovation networks consisting of human and intellectual capital, shaped by social capital and underpinned by financial capital’ (Carayannis et al., 2018 , p. 152–153). Shenzhen’s R&D development is an illustrative case of such perspective, as its R&D activities are largely carried out by industries supported by local financial capital and educated migrants from other cities. As of 2018, most of the R&D activities in the city had been carried out by enterprises. Figure 3 depicts the share of R&D expenditure by sectors and the expenditure per capita of Shenzhen and Hong Kong. Enterprises take up more than 95 per cent of total R&D activities, whereas universities and research institutes take up less than 1 per cent. Figure 3. Share of R&D expenditure by sector and R&D expenditure per capita in Hong Kong and Shenzhen, 2009–2016. Source: Shenzhen Statistics Bureau, 2017 ; Census and Statistics Department of Hong Kong SAR Government (2018). Unit: million USD. Note: For easy comparison, the authors re-grouped data from Shenzhen as follows: university and research institutes as ‘HEIs’ and industrial and service enterprises and construction as ‘businesses’. The authors did not apply any additional grouping to the Hong Kong data. This industry-driven pattern has been confirmed by R&D funding sources and personal distribution. The Shenzhen Statistics Bureau (1991, 2001, 2006, 2011, 2016, 2017, 2018) noted that 87 per cent of R&D personnel worked in medium and large enterprises in Shenzhen by the end of 2016. In addition, the business sector was also the largest performer and funder of research activities, with 94.3 per cent of R&D expenses coming from self-raised funds by enterprises (Shenzhen Statistics Bureau, 2018). Figure 4 further compares R&D expenditure patterns between Shenzhen, Hong Kong, the United States, the European Union (EU) and OECD countries (average). Shenzhen resembles the United States, the EU and OECD countries in terms of its level of R&D expenditure as a percentage of its GDP, with the business sector dominating their local R&Ds. Figure 4. Percentage of R&D expenditure by different sectors and R&D expenditure as a percentage of GDP of the United States, the European Union, OECD average, Shenzhen and Hong Kong in 2017. Source: OECD (2019); Census and Statistics Department of Hong Kong Special Administrative Region (SAR) Government (2018); Shenzhen Statistics Bureau (2017). Note: For easy comparison, the authors labelled private non-profit sectors in the United States, the EU and OECD, whereas unspecified sectors in Shenzhen were labelled as ‘others.’ The official statistics of Shenzhen were re-grouped as follows: university and research institutes as ‘HEIs’ and industrial and service enterprises and construction as ‘businesses’. The official data of Hong Kong included only three sectors: HEIs, businesses and the government. The authors did not apply any additional grouping to the Hong Kong data.
Keywords
- Innovation network
- Quadruple Helix Model
- cross-border cooperation
- higher education institution
- knowledge cluster
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Challenges to research systems, academic research and knowledge production in East Asia: Learning from the past to inform future policy
HORTA, H. (Guest Editor) & MOK, K.-H. (Guest Editor), Apr 2020, Journal of Higher Education Policy and Management, 42, 2.Research output: Other Publications › Special issue (Editor)