Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Gravity Model of Migration× | Location Quotient× | |
|---|---|---|
| Область≠ | Human Geography | Экономика |
| Семейство≠ | Regression model | Process / pipeline |
| Год появления≠ | 1946 | 1960 |
| Автор метода≠ | George Kingsley Zipf (formalized); analogy to Newton's law of gravitation | Developed in regional science; codified by Walter Isard |
| Тип≠ | Spatial-interaction regression model for migration flows | Descriptive index of relative regional concentration |
| Основополагающий источник≠ | Zipf, G. K. (1946). The P1 P2 / D hypothesis: On the intercity movement of persons. American Sociological Review, 11(6), 677–686. DOI ↗ | Isard, W. (1960). Methods of Regional Analysis: An Introduction to Regional Science. Cambridge, MA: MIT Press. ISBN: 9780262090032 |
| Другие названия≠ | Migration Gravity Model, Demographic Gravity Model, Zipf P1P2/D Model, Gravity Model of Spatial Interaction (Migration) | LQ, Coefficient of Localization, Regional Specialization Ratio |
| Связанные≠ | 4 | 3 |
| Сводка≠ | The gravity model of migration explains the volume of movement between two places as proportional to the product of their populations (masses) and inversely proportional to the distance separating them, by direct analogy to Newton's law of universal gravitation. Formalized for intercity movement by George Kingsley Zipf in 1946 and embedded in regional science by Walter Isard, it is the workhorse model of human geography for predicting migration, commuting, and other spatial-interaction flows. | The location quotient (LQ) is a simple descriptive index that measures how concentrated an industry is in a region relative to a larger reference area, usually the nation. It is the ratio of the industry's share of local employment (or output) to its share of national employment. An LQ above one means the region is more specialized in that industry than the nation as a whole; an LQ below one means it is under-represented. |
| ScholarGateНабор данных ↗ |
|
|