This study investigates the relationship between loyalty to supervisor and two employee outcome variables, i.e. job satisfaction and intent to stay. The proposed hypotheses were tested with a sample of 333 employees in the People’s Republic of China. The results indicate that loyalty to supervisor is positively related to job satisfaction and intent to stay. Loyalty to supervisor explained variance in these two outcome variables over and above that explained by organizational commitment. The results also confirm the previous findings that only the three extended loyalty to supervisor dimensions were significantly associated with employee outcomes, while the two original loyalty to supervisor dimensions were not. Implication, limitation and future study direction are also discussed.
Using unmanned aerial vehicles (UAV) as platforms for light detection and ranging (LiDAR) sensors offers the efficient operation and advantages of active remote sensing; hence, UAV-LiDAR plays an important role in forest resource investigations. However, high-precision individual tree segmentation, in which the most appropriate individual tree segmentation method and the optimal algorithm parameter settings must be determined, remains highly challenging when applied to multiple forest types. This article compared the applicability of methods based on a canopy height model (CHM) and a normalized point cloud (NPC) obtained from UAV-LiDAR point cloud data. The watershed algorithm, local maximum method, point cloud-based cluster segmentation, and layer stacking were used to segment individual trees and extract the tree height parameters from nine plots of three forest types. The individual tree segmentation results were evaluated based on experimental field data, and the sensitivity of the parameter settings in the segmentation methods was analyzed. Among all plots, the overall accuracy F of individual tree segmentation was between 0.621 and 1, the average RMSE of tree height extraction was 1.175 m, and the RMSE% was 12.54%. The results indicated that compared with the CHM-based methods, the NPC-based methods exhibited better performance in individual tree segmentation; additionally, the type and complexity of a forest influence the accuracy of individual tree segmentation, and point cloud-based cluster segmentation is the preferred scheme for individual tree segmentation, while layer stacking should be used as a supplement in multilayer forests and extremely complex heterogeneous forests. This research provides important guidance for the use of UAV-LiDAR to accurately obtain forest structure parameters and perform forest resource investigations. In addition, the methods compared in this paper can be employed to extract vegetation indices, such as the canopy height, leaf area index, and vegetation coverage.
The international expansion of Chinese firms is a remarkable phenomenon of contemporary international business. However, international expansion is particularly challenging for firms expanding from emerging market economies such as China because they have relatively few ownership advantages and suffer disadvantages. We apply a corporate entrepreneurship perspective to explore this under‐researched topic via a longitudinal case study of a large Chinese business conglomerate. Thirty‐one semistructured interviews and seven focus‐group discussions were conducted with 55 informants; company documents were also analyzed. We found sophisticated pre‐entry entrepreneurial initiatives are critical for successful internationalization, as they enable emerging market firms to overcome some constraints, leverage their assets, and build competences for international venturing.
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