Predicting the Innovation Activity of Chemical Firms Using an Ensemble of Decision Trees

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F15%3A39899810" target="_blank" >RIV/00216275:25410/15:39899810 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Predicting the Innovation Activity of Chemical Firms Using an Ensemble of Decision Trees

Popis výsledku v původním jazyce

A number of studies are concerned with the analysis of predicting innovation activity, because companies' innovation activity is one of the fundamental determinants for their competitiveness. However, most studies use a linear (logistic) regression modelfor their analysis. This, however, is not able to take into account all the recursive terms concerning a company's innovation activity. Therefore, in the report we demonstrate the use of ensembles of decision trees to model the intrinsic nonlinear characteristics of the innovation process. We apply this method for predicting innovation activity to chemical companies. We show that internal knowledge spillovers were the most important determinant for the chemical firms' innovation activity during the monitored period. Furthermore, R&D intensity, collaboration on innovation and firm size were also important determinants.

Název v anglickém jazyce

Predicting the Innovation Activity of Chemical Firms Using an Ensemble of Decision Trees

Popis výsledku anglicky

A number of studies are concerned with the analysis of predicting innovation activity, because companies' innovation activity is one of the fundamental determinants for their competitiveness. However, most studies use a linear (logistic) regression modelfor their analysis. This, however, is not able to take into account all the recursive terms concerning a company's innovation activity. Therefore, in the report we demonstrate the use of ensembles of decision trees to model the intrinsic nonlinear characteristics of the innovation process. We apply this method for predicting innovation activity to chemical companies. We show that internal knowledge spillovers were the most important determinant for the chemical firms' innovation activity during the monitored period. Furthermore, R&D intensity, collaboration on innovation and firm size were also important determinants.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA14-02836S" target="_blank" >GA14-02836S: Modelování efektů přelévání znalostí v kontextu regionálního a místního rozvoje</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings from 11th International Conference on Innovations in Information Technology

ISBN

978-1-4673-8511-4

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

35-39

Název nakladatele

IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání

New York

Místo konání akce

Dubai

Datum konání akce

1. 11. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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