Effects of the internet on firm location selection
| Authors | Data | Methodology | Main results |
|---|---|---|---|
| Mack (2012) | Firm data in 3,109 US counties | Exploratory techniques; and spatial econometric approaches | The internet reinforces firm cluster in urban areas The impacts are heterogeneous |
| Kim and Orazem (2017) | 63,341 firms in the USA | DID | The internet increases new firm entry to rural areas These rural areas tend to be around the metropolitan area |
| McCoy et al. (2018) | 858 firms of 192 urban fields in Irish | Spatial autoregressive model; and the spatial Durbin model | The internet affects the firm location Pre-existing condition also affects firm location choice |
| Wang et al. (2018) | Community internet firms in Yangzhou | Negative binomial regression model | Internet firms present the largest in the inner suburbs of the city They experience a life cycle of low-high-low form |
| Wei and Cao (2018) | Firm FDI in seven Asian countries | OLS estimation | Internet penetration affects the location selection of Chinese firm FDI The effects are heterogeneous |
| Authors | Data | Methodology | Main results |
|---|---|---|---|
| Firm data in 3,109 US counties | Exploratory techniques; and spatial econometric approaches | The internet reinforces firm cluster in urban areas | |
| 63,341 firms in the USA | DID | The internet increases new firm entry to rural areas | |
| 858 firms of 192 urban fields in Irish | Spatial autoregressive model; and the spatial Durbin model | The internet affects the firm location | |
| Community internet firms in Yangzhou | Negative binomial regression model | Internet firms present the largest in the inner suburbs of the city | |
| Firm FDI in seven Asian countries | OLS estimation | Internet penetration affects the location selection of Chinese firm FDI |