Study of the Factors Influencing Cultural Similarity in the Post-Migration Adaptation Process in the Province of Van Using the GWR Method
As the world becomes increasingly interconnected, migration has gained unprecedented significance, shaping societies, economies, and cultures on a global scale. This introductory exploration delves into the multifaceted dimensions of migration, unraveling its causes, effects, and the intricate web o...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Istanbul University Press
2024-07-01
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| Series: | Coğrafya Dergisi |
| Subjects: | |
| Online Access: | https://cdn.istanbul.edu.tr/file/JTA6CLJ8T5/262BA683AC074386ABE5CF675D6B831C |
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| Summary: | As the world becomes increasingly interconnected, migration has gained unprecedented significance, shaping societies, economies, and cultures on a global scale. This introductory exploration delves into the multifaceted dimensions of migration, unraveling its causes, effects, and the intricate web of interactions it weaves across nations and continents. In this study, the factors influencing cultural similarity in the post-migration adaptation process of individuals migrating from first- and second-degree border provinces to the province of Van were examined using Ordinary Least Squares and Geographically Weighted Regression methods. The aim of this study is to examine the factors that influence cultural similarity in the process of adaptation in migration to the province of Van and to determine which of the methods used gives stronger results. In the study, face-to-face interviews were conducted with 440 individuals, and it was observed that the Geographically Weighted Regression method gave stronger results in terms of AIC, AICc, BIC, RSS, R2 and Adj. R2 . In addition, the effect and significance of the independent variables according to provinces and districts are among the other objectives of the study. In this direction, the effect and significance of the independent variables are given by visualising them on the maps according to the provinces and districts. |
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| ISSN: | 1305-2128 |