A spatial analysis of the determinants of Inter-regional migration: evidence from Ghana

Sub-Saharan Africa has experienced a rapid population increase and growing urbanization rates in recent years and is bound to have the world's largest urban population. If no steps are taken against it, the fast rise in the urban population will result in severe consequences for urban localities in the developing countries located in this region. Along with the natural population increase, internal migration is one prime reason for a fast-rising urbanization process. Since this type of migration is very common in developing countries, this following paper conducts a spatial analysis of inter-regional migration with special reference to Ghana. Specifically, it analyzes the Ghana's migration patterns in Ghana by visualizing the regional differences in net migration and the major migration flows from one region to another. Data for this analysis were collected from a population census and a household survey. A cross-sectional regression analysis was conducted to examine which factors explain inter-regional migration flows in the country. The regression model employed in the analysis is based on the gravity model of migration, which explains how the size of and the distance between two places affects the movement between them, and added the rate of urbanization as well as the average annual income per capita of both regions. The regression results reveal that the distance between two administrative regions in Ghana and the birth region's urbanization rate refrain people from migrating to other regions. In contrast, the urbanization rate and the average income of the destination region are positively associated with the inflow of migrants. Nevertheless, due to the data's limitations, the nexus between migration flows and regional disparities cannot be fully investigated. Therefore, this paper calls for more research to be done in this field

Spatial dependence in the regional innovation performance of small- and medium sized enterprises : A spatial econometric approach to identifying the drivers of SME innovation in European NUTS regions

Being a crucial sector in Europe’s economy, small and medium-sized enterprises (SMEs) require involvement in innovative activities to perpetuate their competitiveness. Nevertheless, European-wide funding programs that aim to foster innovation at the regional level have been criticized for not being adequately tailored to SMEs’ innovation patterns and dynamics. Against this background, this thesis sheds light on the innovation processes occurring among SMEs by explaining their innovation performance as a function of potential innovation drivers. Mindful of the relevance of geography in innovative activities, this thesis investigates whether SME innovation performance in a European region is subject to spatial dependence.   Firstly, the presence of spatial dependence is determined using Moran’s I to indicate the magnitude and significance of spatial autocorrelation in the level of SME innovation performance. In the second step, a cross-sectional spatial regression analysis examines the drivers of the innovation performance while accounting for spatial autoregressive processes. This analysis follows a bottom-up approach proposed by Elhorst (2010) to specify the suitable model for SME product and business process innovations. Additionally, the Generalized Spatial Two-stage Least Squares (GS2SLS) method accounts for heteroskedasticity of any form in the disturbances. This paper finds evidence for the presence of spatial dependence in the region’s level of SME product and business process innovation performance, implying that regions with high levels of SME innovation performance tend to be surrounded by regions with high levels and vice versa. The results from the regression analysis indicate that SMEs draw from non-R&D activities and collaboration, which offset the disadvantages these firms face. Moreover, while public and private R&D expenditures still play a role in product innovation, at least partly, the involvement in R&D activities is less important for SMEs introducing process innovation. Based on the results obtained, this paper proposes policy adaptations allowing a better environment for SMEs to participate in innovative activities

Spatial dependence in the regional innovation performance of small- and medium sized enterprises : A spatial econometric approach to identifying the drivers of SME innovation in European NUTS regions

Being a crucial sector in Europe’s economy, small and medium-sized enterprises (SMEs) require involvement in innovative activities to perpetuate their competitiveness. Nevertheless, European-wide funding programs that aim to foster innovation at the regional level have been criticized for not being adequately tailored to SMEs’ innovation patterns and dynamics. Against this background, this thesis sheds light on the innovation processes occurring among SMEs by explaining their innovation performance as a function of potential innovation drivers. Mindful of the relevance of geography in innovative activities, this thesis investigates whether SME innovation performance in a European region is subject to spatial dependence.   Firstly, the presence of spatial dependence is determined using Moran’s I to indicate the magnitude and significance of spatial autocorrelation in the level of SME innovation performance. In the second step, a cross-sectional spatial regression analysis examines the drivers of the innovation performance while accounting for spatial autoregressive processes. This analysis follows a bottom-up approach proposed by Elhorst (2010) to specify the suitable model for SME product and business process innovations. Additionally, the Generalized Spatial Two-stage Least Squares (GS2SLS) method accounts for heteroskedasticity of any form in the disturbances. This paper finds evidence for the presence of spatial dependence in the region’s level of SME product and business process innovation performance, implying that regions with high levels of SME innovation performance tend to be surrounded by regions with high levels and vice versa. The results from the regression analysis indicate that SMEs draw from non-R&D activities and collaboration, which offset the disadvantages these firms face. Moreover, while public and private R&D expenditures still play a role in product innovation, at least partly, the involvement in R&D activities is less important for SMEs introducing process innovation. Based on the results obtained, this paper proposes policy adaptations allowing a better environment for SMEs to participate in innovative activities

Reduction of cone‐beam CT artifacts in a robotic CBCT device using saddle trajectories with integrated infrared tracking

International audienceAbstract Background Cone beam computed tomography (CBCT) is widely used in many medical fields. However, conventional CBCT circular scans suffer from cone beam (CB) artifacts that limit the quality and reliability of the reconstructed images due to incomplete data. Purpose Saddle trajectories in theory might be able to improve the CBCT image quality by providing a larger region with complete data. Therefore, we investigated the feasibility and performance of saddle trajectory CBCT scans and compared them to circular trajectory scans. Methods We performed circular and saddle trajectory scans using a novel robotic CBCT scanner (Mobile ImagingRing (IRm); medPhoton, Salzburg, Austria). For the saddle trajectory, the gantry executed yaw motion up to using motorized wheels driving on the floor. An infrared (IR) tracking device with reflective markers was used for online geometric calibration correction (mainly floor unevenness). All images were reconstructed using penalized least‐squares minimization with the conjugate gradient algorithm from RTK with voxel size. A disk phantom and an Alderson phantom were scanned to assess the image quality. Results were correlated with the local incompleteness value represented by , which was calculated at each voxel as a function of the source trajectory and the voxel's 3D coordinates. We assessed the magnitude of CB artifacts using the full width half maximum (FWHM) of each disk profile in the axial center of the reconstructed images. Spatial resolution was also quantified by the modulation transfer function at 10% (MTF10). Results When using the saddle trajectory, the region without CB artifacts was increased from 43 to 190 mm in the SI direction compared to the circular trajectory. This region coincided with low values for . When was larger than 0.02, we found there was a linear relationship between the FWHM and . For the saddle, IR tracking allowed the increase of MTF10 from 0.37 to 0.98 lp/mm. Conclusions We achieved saddle trajectory CBCT scans with a novel CBCT system combined with IR tracking. The results show that the saddle trajectory provides a larger region with reliable reconstruction compared to the circular trajectory. The proposed method can be used to evaluate other non‐circular trajectories