Managing related variety in smart specialisation industries : company specific development path
Fragment książki (Materiały konferencyjne)
MNiSW
15
WOS
| Status: | |
| Autorzy: | Pylak Korneliusz, Majerek Dariusz |
| Dyscypliny: | |
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| Wersja dokumentu: | Drukowana | Elektroniczna |
| Arkusze wydawnicze: | 0,5 |
| Język: | angielski |
| Strony: | 1285 - 1294 |
| Web of Science® Times Cited: | 0 |
| Bazy: | Web of Science |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | 11th International Days of Statistics and Economics |
| Skrócona nazwa konferencji: | 11th IDSE 2017 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 16 sierpnia 2017 do 17 sierpnia 2017 |
| Miasto konferencji: | Praga |
| Państwo konferencji: | CZECHY |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| The aim of this paper is to create a new, structured definition of different industries’ related varieties involved in regional smart specialisations. To define related variety in each industry, we used machine-learning-method decision trees. The input and target variables are the number of companies from 86 industries located in 2,531 communities in Poland. Decision trees allow us to predict how many companies from each industry exist in communities, given the precise number of companies from related industries and the number of communities in which these relationships occur. The trees indicate the most common structures of related industries. Our findings confirm that related variety differs in size and scope for every industry and includes companies both within and outside the natural value chain (suppliers and clients). The findings prove the utility of the new definition of related variety, as defining related variety properly and precisely may facilitate the process of implementing and developing smart specialisations in regions. |
