The relationship between regional compactness and regional innovation capacity (RIC): Empirical evidence from a national study

Hamidi, Shima; Zandiatashbar, Ahoura; Bonakdar, Ahmad

doi:10.1016/j.techfore.2018.07.026

Cited by 61 publications

(39 citation statements)

References 79 publications

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“…The significant influence of universities and research institutions on innovation is confirmed by many studies [25,[64][65][66]. Hamidi examined and verified a significant positive correlation between university R&D and local innovation capabilities [42]. These studies found that R&D investment and knowledge economy play a crucial role, and there is a potential causal relationship between these components and innovation.…”

Section: The Effects Of Built Environment On the Location Choice And mentioning

confidence: 80%

“…The literature on high-tech firms' location choice and innovation emphasizes the role of built environment factors. A study by Shima showed that regional compactness has a significant positive impact on innovative firms and regional innovation capacity [42,43]. Li found that accessibility can significantly affect the location choice for high-tech firms [29].…”

Section: Introductionmentioning

confidence: 99%

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Relationship Between the Built Environment and the Location Choice of High-Tech Firms: Evidence from the Pearl River Delta

Wang

et al. 2019

Sustainability

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With the transition in the regional development discourse to knowledge- and innovation-based economics, the cultivation of innovation capacity has gained importance as an initiative to enhance regional sustainability and has emerged as a policy goal. An understanding of the formation of innovation clusters is critical to the cultivation of regional innovation capabilities. Except for the location and regional development conditions’ factors, researchers emphasize a built environment’s role in the formation of innovation clusters. Based on the spatial database of 12,516 high-tech firms in 2017 in the Pearl River Delta (PRD), this study developed a conceptual framework for the built environment. The framework comprises living, service, perceptual, industrial, and physical aspects. The direction and intensity of the correlation between built environment factors and high-tech firms are discussed using the spatial regression model and geographical detector (GD) technique. The results show a highly concentrated spatial distribution pattern of high-tech firms in the PRD. A significant county-level spatial autocorrelation is revealed through Moran’s I. According to the model, we determine the positive impacts of technology support, transport infrastructure, and living service levels on the agglomeration of high-tech firms as well as the negative impact of the public service level. The GD’s result demonstrates different levels of impact intensity of built environmental factors. We argue that a comprehensive understanding of the influence of built environment factors on innovation agglomeration will help policymakers develop targeted policies to foster local innovation capabilities and promote sustainable regional development.

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Section: The Effects Of Built Environment On the Location Choice And mentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Relationship Between the Built Environment and the Location Choice of High-Tech Firms: Evidence from the Pearl River Delta

Wang

et al. 2019

Sustainability

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“…Drawing on the Small Business Innovation Research (SBIR) database, scholars found more award-winning innovations were developed in dense, mixed-use and walkable neighborhoods (and regions) that also benefit from high-quality transit service , 2017a, 2017bHamidi, Zandiatashbar, and Bonakdar 2018;Zandiatashbar and Hamidi 2018).…”

Section: Introductionmentioning

confidence: 99%

The Missing Link between Place and Productivity? The Impact of Transit-Oriented Development on the Knowledge and Creative Economy

Zandiatashbar

Hamidi

Foster

et al. 2019

Journal of Planning Education and Research

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Emerging research suggests that planners and policy makers should explore the expanded role Transit-Oriented Development (TOD) plays in promoting innovation and economic growth. TOD station characteristics including accessibility, walkability, density, and mixed uses may create environments beneficial for creative and knowledge industries. However, the evidence linking place to productivity, as measured by firm sales volume is lacking. Using cluster analysis and Propensity Score Matching for national-level data, this research tests these relationships. Findings indicate that firms located in dense, mixed use, and walkable TODs with higher levels of activity experience increased sales. Hence, TOD and knowledge-based economic development strategies should be planned in tandem to maximize outcomes.

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“…A country's technological innovation activities always have obvious regional characteristics [1][2][3][4], and the efficiency of regional innovation can differ among regions [5][6][7][8]. Technological innovation can be seen as a main driver of regional development and economic growth [9], but at the same time can also bring sincere damage to the natural environment when it is unsustainable [10].…”

Section: Introductionmentioning

confidence: 99%

“…Sustainable innovation efficiencies differ to a considerable degree among Chinese regions 2. Sustainable innovation efficiency scores are much lower when undesirable outputs are taken into account 3. Sustainable innovation efficiency in China has risen in recent years.…”

mentioning

confidence: 99%

Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs

Bossink

Chen

2019

Sustainability

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An efficiency evaluation of China's regional sustainable innovation, evaluating industrial waste and total energy consumption, is the main research subject in this paper. It focuses on a regional measurement and comparison of these undesirable outputs of Chinese firm activities, such as industrial SO 2 and CO 2 emissions. By applying a data envelopment analysis-slack-based measure (DEA-SBM) model with undesirable outputs indicators, the regional innovation efficiency was evaluated for 30 provinces in China, from 2002 to 2014. The results indicate that the sustainable innovation efficiency of overall China is still relatively low, and varies significantly in different regions. Central and Western China have similar sustainable innovation efficiencies, which are much lower than the sustainable innovation efficiency in Eastern China. Furthermore, the data indicate that regional sustainable innovation efficiency disparities among these three areas are decreasing. Based on these findings, reasons for the sustainable innovation efficiency gap among the different regions were analyzed. To scholars, this paper extends the research on regional sustainable innovation efficiency by implementing an undesirable output perspective to the DEA-SBM model. The findings also provide Chinese policy makers with useful decision support insights for regional sustainable innovation, and energy conservation and emission reduction policies.Sustainability 2020, 12, 31 2 of 21 differences can be addressed [15][16][17]. Research on regional innovation efficiency has gained increasing attention in recent years [18][19][20], but to the best of our knowledge, very few studies have been conducted to quantitatively evaluate sustainable innovation efficiency in China, by means of focusing on undesirable outputs like industrial SO 2 and CO 2 emissions [21,22]. Our study aims to contribute to the knowledge in this area, and does this by means of measuring and comparing unsustainable, unwanted, and undesirable outcomes/byproducts of Chinese regions' innovative firm activities. By evaluating the regional sustainable innovation efficiency of 30 provinces in China from 2002 to 2014, using the slack-based measure (SBM) model, this study focuses on the following research question: what are the differences between sustainable innovation efficiencies of different regions in China and which trends in these differences can be estimated?How to deal with SO 2 and CO 2 emissions and with related climate change has become one of the most urgent challenges of today's world. For example, it has been reported that global CO 2 emissions from fuel combustion has increased from 26,177 Mt in 2004 to 32,190 Mt in 2013. Many countries have committed to controlling SO 2 and CO 2 emissions and aim to develop a no-to low-emissions economy. In 2015, the Paris Climate Change Conference adopted the "Paris Agreement" to deal with climate change after 2020 [24]. More than 170 countries jointly signed the Paris Agreement in 2016. China and the United States officially ratified the...

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The relationship between regional compactness and regional innovation capacity (RIC): Empirical evidence from a national study

Cited by 61 publications

References 79 publications

Relationship Between the Built Environment and the Location Choice of High-Tech Firms: Evidence from the Pearl River Delta

Relationship Between the Built Environment and the Location Choice of High-Tech Firms: Evidence from the Pearl River Delta

The Missing Link between Place and Productivity? The Impact of Transit-Oriented Development on the Knowledge and Creative Economy

Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs

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