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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ivan, Savin | - |
dc.contributor.author | Maria, Novitskaya | - |
dc.date.accessioned | 2023-04-13T03:37:50Z | - |
dc.date.available | 2023-04-13T03:37:50Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://link.springer.com/article/10.1007/s40821-023-00239-2 | - |
dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/7883 | - |
dc.description | CC BY | vi |
dc.description.abstract | The phenomenon of fast-growing companies exhibiting sustained growth and creating disproportionally many new jobs, so-called “gazelles”, has been widely analyzed in the literature. The criteria defining “gazelles”, however, lack a consensus, while it cannot be ruled out that superior performance of these companies is just good luck. We use large firm-level datasets for Russia and Spain and conduct a Monte Carlo experiment with first-order Markov chains to derive a definition of “gazelle” companies and ensure that their existence cannot be explained by chance only. | vi |
dc.language.iso | en | vi |
dc.publisher | Springer | vi |
dc.subject | Data-driven definitions | vi |
dc.subject | application for Russia and Spain | vi |
dc.title | Data-driven definitions of gazelle companies that rule out chance: application for Russia and Spain | vi |
dc.type | Book | vi |
Appears in Collections | ||
OER - Kinh tế và Quản lý |
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