El emprendimiento de base tecnológica y su punto de encuentro con la convergencia tecnocientífica: una revisión a partir del algoritmo Tree of Science

Sánchez, Edward Andrés Benavides; Ruíz, Camilo Andrés Castro; Narváez, Miguel Ángel Brand

doi:10.22430/24223182.2153

Cited by 4 publications

(1 citation statement)

References 79 publications

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“…Benavides-Sánchez et al [43] studied business incubators and the role developed by universities as a catalyst between student entrepreneurs, teachers, researchers, and investors. The need was found to build multidisciplinary work teams, with collaborative work networks.…”

Section: Introductionmentioning

confidence: 99%

Typology of Business Incubators in Spain according to the Stages of Startups Incubation

Asensio-Ciria,

De-Pablos-Heredero,

Blanco Jiménez

et al. 2024

Preprint

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The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

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Section: Introductionmentioning

confidence: 99%

Typology of Business Incubators in Spain according to the Stages of Startups Incubation

Asensio-Ciria,

De-Pablos-Heredero,

Blanco Jiménez

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Foresight study using scenarios and the Delphi method in the leather agroindustrial chain to 2035 - Alignment of results with open innovation

Sossa,

Posada,

Montoya

et al. 2024

Journal of Open Innovation: Technology, Market, and Complexity

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Typology of Business Incubators in Spain According to the Stages of Startups Incubation

Asensio-Ciria,

De-Pablos-Heredero,

Blanco Jiménez

et al. 2024

Administrative Sciences

View full text Add to dashboard Cite

The aim of this work was to classify the business incubators in Spain according to the four phases of the startup’s incubation process. Considering that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the business incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis has been applied. All the incubation variables were used simultaneously, reducing their number and grouping them into factors. Finally, the cases were grouped according to these latent variables. Principal component analysis reduced dimensionality to eight factors with a 74% explained variance. Factor 1 was positively related to pre-incubation variables; factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3, named activity monitoring and control, was related to phase 3, or basic incubation variables. Cluster analysis facilitates the grouping of business incubators into three clusters: Group 1 (16% of the total), incubators with strong deficits in incubation phases 1, 2, and 3. They are small-sized business incubators, often located in rural areas or cities, with a low graduation rate. Group 2 (30%), business incubators with a very high graduation rate and strongly positive values in factors 1 and 2. Factor 3, although positive, is susceptible to improvement. They are the largest group of business incubators and usually located in industrial and technological parks. Group 3 (54%) is the majority, with values close to clusters 2 and 3.

show abstract

El emprendimiento de base tecnológica y su punto de encuentro con la convergencia tecnocientífica: una revisión a partir del algoritmo Tree of Science

Cited by 4 publications

References 79 publications

Typology of Business Incubators in Spain according to the Stages of Startups Incubation

Typology of Business Incubators in Spain according to the Stages of Startups Incubation

Foresight study using scenarios and the Delphi method in the leather agroindustrial chain to 2035 - Alignment of results with open innovation

Typology of Business Incubators in Spain According to the Stages of Startups Incubation

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