Agglomeration of knowledge intensive business services and urban productivity

Zhang, Cui

doi:10.1111/pirs.12204

Cited by 19 publications

(17 citation statements)

References 73 publications

(126 reference statements)

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“…KIBS are more intensively engaged in training activities than their manufacturing sectors (Wong & He, 2005). KIBS has a plenty of opportunities to learn knowledge from both inside and outside industries (Zhang, 2016). Thus, KIBS can obtain knowledge through training courses, including physically vocational training programmes and e-learning courses.…”

Section: The Indicators Of Knowledge Intensity and Economic Performanmentioning

confidence: 99%

The knowledge intensity and the economic performance in Taiwan’s knowledge intensity business services

Chung

Tseng

2019

Economic Research-Ekonomska Istraživanja

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The service sector plays a key role to employment growth and increased public well-being in OECD countries. The service industries contributed more than 63% of GDP in 2016 and have become the core of economy in Taiwan. Within the service sectors, knowledge-intensive business services (KIBS) particularly illustrate higher levels of productivity and profitability. Moreover, due to lack of the clear measurements of the knowledge intensity with prior investigations in KIBS, the aim of this article is to explore the knowledge intensity of Taiwan's KIBS. This study then further probes into the relationship between knowledge intensity and economic performance. Panel data from 13 service sectors in Taiwan during the period 2007-2015 is analysed with a fixed effect model. This empirical research shows four findings: first, 13 industries are classified into three groups as high, low, and no level of knowledge intensity; second, most of the level of knowledge intensity has been increased from stage one to stage two; third, education level and vocational training rate positively influence productivity; and, finally, the percentage of knowledge workers and vocational training rate have a positive effect on the margin rate.

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Section: The Indicators Of Knowledge Intensity and Economic Performanmentioning

confidence: 99%

The knowledge intensity and the economic performance in Taiwan’s knowledge intensity business services

Chung

Tseng

2019

Economic Research-Ekonomska Istraživanja

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“…To analyze the determinants of RL flows from a dynamic perspective, we estimated the full model for two subperiods (2013-2014 and 2016-2017) and compared their parameters over time. We took 2-year lagged independent variables to address the endogeneity and reverse causality concerns (Fernandez et al, 2016, Zhang, 2016, Gui et al, 2018. Table 7 presents the estimation results for different subperiods.…”

Section: Estimation For Different Subperiodsmentioning

confidence: 99%

Research leadership flow determinants and the role of proximity in research collaborations

Qingpeng

2019

Asso for Info Science & Tech

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Characterizing the leadership in research is important to revealing the interaction pattern and organizational structure through research collaboration. This research defines the leadership role based on the corresponding author's affiliation, and presents the first quantitative research on the factors and evolution of 5 proximity dimensions (geographical, cognitive, institutional, social, and economic) of research leadership. The data to capture research leadership consist of a set of multi-institution articles in the fields of "Life Sciences & Biomedicine," "Technology," "Physical Sciences," "Social Sciences," and "Humanities & Arts" during 2013-2017 from the Web of Science Core Citation Database. A Tobit regression-based gravity model indicates that the mass of research leadership of both the leading and participating institutions and the geographical, cognitive, institutional, social, and economic proximities are important factors for the flow of research leadership among Chinese institutions. In general, the effect of these proximities for research leadership flow has been declining recently. The outcome of this research sheds light on the leadership evolution and flow among Chinese institutions, and thus can provide evidence and support for grant allocation policies to facilitate scientific research and collaborations.

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“…In recent years, empirical analysis in this field has only begun to emerge in China, focusing mainly on the provincial scale [15] and the county-city scale in some provinces [16][17][18]. Zhang [3] used employment density to measure KIBS agglomeration of 280 prefecture-level cities and discovered that KIBS was concentrated mainly in cities with high administrative rank.…”

Section: Geographical Concentration Of Knowledge-and Technology-intenmentioning

confidence: 99%

“…However, the contribution of developing countries to global KIBS growth continues to increase. The growth rate of KIBS added value in developing countries has exceeded that in developed countries since 2003, and the share of KIBS added value in developing countries has increased from 10% in 2003 to approximately 21% in 2012 [3].…”

Section: Introductionmentioning

confidence: 99%

Geographical Concentration of Knowledge- and Technology-Intensive Industries and City Innovation in China

Liu

et al. 2019

Sustainability

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Economic transformation and re-industrialization constantly change the geographical landscape of knowledge- and technology-intensive industries (KTI) globally, and the role of KTI agglomeration in city innovation is becoming increasingly decisive. Based on the employment data with a two-digit code in China’s 2010 Population Census, this paper compares the spatial difference between absolute and relative concentration of knowledge-intensive business service (KIBS) and technology-intensive manufacturing (TIM) in prefecture-level units, and interprets the diverse impact of KIBS and TIM specialisation on innovation in 286 prefecture-level cities. Results indicate that KIBS is concentrated mainly in the provincial capital cities, while the level of KIBS specialisation exceeds the national average in some border cities of the northwestern region and resource-based cities of the northeastern region. Unlike KIBS, TIM is highly concentrated in the Yangtze River Delta, the Pearl River Delta, and the Beijing–Tianjin and Shandong Peninsula urban agglomerations. KIBS specialisation matters more in boosting city innovation than does TIM specialisation, and TIM specialization exerts a significant positive spatial spillover effect on city innovation. Our empirical results could be considered by policy-makers for the development of KTI and the promotion of city innovation.

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Agglomeration of knowledge intensive business services and urban productivity

Cited by 19 publications

References 73 publications

The knowledge intensity and the economic performance in Taiwan’s knowledge intensity business services

The knowledge intensity and the economic performance in Taiwan’s knowledge intensity business services

Research leadership flow determinants and the role of proximity in research collaborations

Geographical Concentration of Knowledge- and Technology-Intensive Industries and City Innovation in China

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