The typology of technology clusters and its evolution — Evidence from the hi-tech industries

He, Jinliao; Fallah, M. Hosein

doi:10.1016/j.techfore.2011.01.005

Cited by 42 publications

(19 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…While most of the past research has argued that a specific model fits a specific case (De Marchi & Grandinetti, 2014) or that specific cases are unique and match the mix of several models (He & Fallah, 2011), we argue that a specific region can be managed by different models simultaneously and cumulatively. In our empirical study, we argue that the greatly localized GIANT model and the localized Grenoble model are two co-existing TIMs developed around the CEA (Figure 2).…”

Section: Grenoble Model: Localized Clustermentioning

confidence: 67%

“…Moreover, we encourage scholars to monitor the progress of socioeconomic and entrepreneurial indicators in longitudinal studies, which would put in perspective the cluster life cycle described by He and Fallah (2011). It would be interesting to study the embryonic, established, mature, and declining stages of a cluster and to also observe how policymakers anticipate the decline in the life cycle of industrial districts (Corò & Grandinetti, 2001) by creating new TIMs in the same geographical area.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Grenoble–GIANT Territorial Innovation Models: Are investments in research infrastructures worthwhile?

Scaringella

Chanaron

2016

Technological Forecasting and Social Change

View full text Add to dashboard Cite

Over the past decades, the EU heavily invested in Research Infrastructures (RI). What are the expected returns of such investments? In the present article we address the question of returns on public funds/public infrastructures. We consider the role of RI and universities from an economic, social, and entrepreneurial perspective from various Territorial Innovation Models (TIMs): (1) Italian industrial districts, (2) innovative milieus, (3) regional innovation systems, (4) new industrial spaces, and (5) regional clusters. We conducted our empirical study on Grenoble Isère Alpes Nanotechnologies (GIANT), which is composed of large scientific instruments, universities, and engineering and management schools. Our microeconomic methodology measured the socioeconomic and entrepreneurial effects of GIANT with respect to budget, employment, and spin-off generation. We contribute to the existing body of knowledge on TIMs by (1) comparing the long-term investments to the generation of wealth, the creation of employment, and the development of start-ups; (2) adding new insights to the debate opposing positive and negative impacts empirical studies; and (3) offering recommendations for the use of public resources. In our discussion, we compare the GIANT model as a very localized RI-university club to the Grenoble model as localized cluster.

show abstract

Section: Grenoble Model: Localized Clustermentioning

confidence: 67%

Section: Resultsmentioning

confidence: 99%

Grenoble–GIANT Territorial Innovation Models: Are investments in research infrastructures worthwhile?

Scaringella

Chanaron

2016

Technological Forecasting and Social Change

View full text Add to dashboard Cite

show abstract

“…Dynamic overlays that can be accessed interactively on the internet provide the user with options to trace technological developments and develop new perspectives reflexively. The use of Rao-Stirling diversity in this study can be considered as a case in point: the literature pointed us to considering variety versus the loss of variety in shake-out phases as central to techno-economic developments (Anderson & Tushman, 1990;He & Fallah, 2011), but the data allowed us to operationalize this in relation to the new instruments. The extension beyond two maps to be recombined follows as a progressive research agenda for quantitative innovation studies (Rotolo et al, in preparation).…”

Section: Discussionmentioning

confidence: 99%

Patents as instruments for exploring innovation dynamics: geographic and technological perspectives on “photovoltaic cells”

et al. 2014

View full text Add to dashboard Cite

The recently developed Cooperative Patent Classifications (CPC) of the U.S. Patent and Trade Office (USPTO) and the European Patent Office (EPO) provide new options for an informed delineation of samples in both USPTO data and the Worldwide Patent Statistical Database (PatStat) of EPO. Among the "technologies for the mitigation of climate change" (class Y02), we zoom in on nine material technologies for photovoltaic cells; and focus on one of them (CuInSe 2 ) as a lead case. Two recently developed techniques for making patent maps with interactive overlays-geographical ones using Google Maps and maps based on citation relations among International Patent Classifications (IPC)-are elaborated into dynamic versions that allow for online animations and comparisons by using split screens. Various forms of animation are discussed. The longitudinal development of Rao-Stirling diversity in the IPC-based maps provided us with a heuristics for studying technological diversity in terms of generations of the technology. The longitudinal patterns are clear in USPTO data more than in PatStat data because PatStat aggregates patent information from countries in different stages of technological development, whereas one can expect USPTO patents to be competitive at the technological edge.

show abstract

“…Businesses participate in a cluster to take advantage of the quality of available resources, reduce the costs of transactions and benefit from the transfer of knowledge that fosters the development of new and creative ideas (He and Fallah, 2011;Lamprinopoulou and Tregear, 2011). Being part of a cluster provides access to common resources, interactions with neighbouring businesses as well as a sense of confidence that improves business transactions (Gnyawali and Srivastava, 2013).…”

Section: Specificities Of High Technology Smesmentioning

confidence: 99%

Opportunity recognition by international high-technology start-up and growth photonics firms

Veilleux¹,

Béliveau²,

Haskell³

2018

IJEIM

View full text Add to dashboard Cite

The typology of technology clusters and its evolution — Evidence from the hi-tech industries

Cited by 42 publications

References 7 publications

Grenoble–GIANT Territorial Innovation Models: Are investments in research infrastructures worthwhile?

Grenoble–GIANT Territorial Innovation Models: Are investments in research infrastructures worthwhile?

Patents as instruments for exploring innovation dynamics: geographic and technological perspectives on “photovoltaic cells”

Opportunity recognition by international high-technology start-up and growth photonics firms

Contact Info

Product

Resources

About