Impact of US Economic Crises on University Research and Development Investments

Daim, Tuğrul U.; Özdemir, Dilek

doi:10.1007/s13132-012-0135-2

Cited by 9 publications

(5 citation statements)

References 33 publications

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“…----Insert Figure 2 adobe here ----- (Daim and Ozdemir, 2012;Siegel et al 2004;Simha, 2005), which outstrips their entrepreneurial activities (Guerrero and Urbano, 2012). For instance, in this case, the relationship between expenses and universities' activities is positive and significant only for teaching and research activities.…”

Section: Exploring the Economic Impact Of United Kingdom's Public Unimentioning

confidence: 88%

“…This variable encompasses the salaries of university staff and the operating expenses associated with the outcomes for a particular year (Daim and Ozdemir, 2012;Elliott et al, 1988;Landry et al, 2006;O'Shea et al, 2005). Based on the resource-based view approach, this variable serves as a proxy for the internal factors (resources and capabilities) that contribute to generate the entrepreneurial university's outcomes (Wernerfelt, 1995).…”

Section: Variablesmentioning

confidence: 99%

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Economic impact of entrepreneurial universities’ activities: An exploratory study of the United Kingdom

2015

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Throughout economic history, institutions have established the rules that shape human interaction. In this sense, political, socio-cultural, and economic issues respond to particular forces: managed economy or entrepreneurial economy. In the entrepreneurial economy, the dominant production factor is knowledge capital that is the source of competitive advantage, which is complemented by entrepreneurship capital, representing the capacity to engage in and generate entrepreneurial activity. Thus, an entrepreneurial economy generates scenarios in which its members can explore and exploit economic opportunities and knowledge to promote new entrepreneurial phenomena that have not been previously visualised. In this context, the entrepreneurial university serves as a conduit of spillovers contributing to economic and social development through its multiple missions of teaching, research, and entrepreneurial activities. In particular, the outcomes of its missions are associated with the determinants of production functions (e.g. human capital, knowledge capital, social capital, and entrepreneurship capital). All these themes are still considerate potentially in the research agenda in academic entrepreneurship literature. This paper modestly tries to contribute to a better understanding of the economic impact of entrepreneurial universities' teaching, research, and entrepreneurial activities. Taking an endogenous growth perspective, the proposed conceptual model is tested using data collected from 2005-2007 for 147 universities located in 74 Nomenclature of Territorial Units for Statistics-3 (NUTS-3) regions of the United Kingdom. The results of this exploratory analysis show the positive and significant economic impact of teaching, research, and entrepreneurial activities. Interestingly, the higher economic impact of the United Kingdom's entrepreneurial universities (the Russell group) is explained by entrepreneurial spin-offs. However, our control group composed by the rest of the country's universities, the highest economic impact is associated with knowledge transfer (knowledge capital).

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Section: Exploring the Economic Impact Of United Kingdom's Public Unimentioning

confidence: 88%

Section: Variablesmentioning

confidence: 99%

Economic impact of entrepreneurial universities’ activities: An exploratory study of the United Kingdom

2015

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“…As a result, four parameters (e.g., economy, public facility, habitation, and environments) were used in this study (Table 1). Economic parameters included government expenditure and resident income, which may affect financial status of local universities through tax investment at the national and local scales, respectively [27,28]. Public facilities covered aspects of communication, transportation, health care, education, and regional culture, which were all related to university students [29][30][31].…”

Section: Data About City Variablesmentioning

confidence: 99%

The Relationship between the Facial Expression of People in University Campus and Host-City Variables

2020

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Public attitudes towards local university matters for the resource investment to sustainable science and technology. The application of machine learning techniques enables the evaluation of resource investments more precisely even at the national scale. In this study, a total number of 4327 selfies were collected from the social network services (SNS) platform of Sina Micro-Blog for check-in records of 92 211-Project university campuses from 82 cities of 31 Provinces across mainland China. Photos were analyzed by the FireFACETM-V1.0 software to obtain scores of happy and sad facial expressions and a positive response index (PRI) was calculated (happy-sad). One-way analysis of variance indicated that both happy and PRI scores were highest in Shandong University and lowest in Harbin Engineering University. The national distribution of positive expression scores was highest in Changchun, Jinan, and Guangzhou cities. The maximum likelihood estimates from general linear regression indicated that the city-variable of the number of regular institutions of higher learning had the positive contribution to the happy score. The number of internet accesses and area of residential housing contributed to the negative expression scores. Therefore, people tend to show positive expression at campuses in cities with more education infrastructures but fewer residences and internet users. The geospatial analysis of facial expression data can be one approach to supply theoretical evidence for the resource arrangement of sustainable science and technology from universities.

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“…Finally, we use a dummy variable for the "Post-crisis" period (2008-2013), in line with other studies in the academic literature (Klapper and Love, 2011;Furceri and Mourougane, 2012;Daim and Ozdemir, 2015;Hud and Hussinger, 2015;Mina and Rocchetta, 2016). This dummy takes the value 1 for each of the years 2008-2013.…”

Section: Variables and Empirical Modelmentioning

confidence: 99%