Long-Term Orientation As A Determinant Of Relationship Quality Between Channel Members

This study assesses the effects of Long-Term Orientation culture on inter-organizational trust and conflict. This research examines the role of one important cultural factor, namely long-term orientation, as it relates to contractual relationships between manufacturers and their suppliers. As LTO cultures have become accepted as a crucial factor for describing nations, this study should prove invaluable to our understanding of inter-organizational relationships affected by differing levels of long-term orientation. The authors investigate the effects of LTO in the relationship between a manufacturer and its supplier. These results reveal that, LTO culture significantly affects the relationships between channel members. In particular, high LTO culture positively affects the generation of trust. Whereas high LTO culture suppresses the conflict between channel members, low LTO cultures do not suppress conflict between channel members

The Effect Of Group-Orientation Culture On Inter-Organizational Cooperation Mechanisms

Cooperation between exchange parties becomes a center for inter-organizational relationship. Cooperation reduces the attractiveness of opportunistic behavior that seeks short-term benefits, so it has been identified as a key factor for inter-organizational cooperation. Although several factors affecting cooperative relationship have been studied, the majority of inter-organizational studies are conducted on the basis of an individualistic perspective view of Western culture. This study introduces group-orientation culture and tries to enhance the understanding the effect of group-orientation culture on inter-organizational cooperation in the relationship between exchange parties. This study suggests that group-orientation culture influences the generation of informal cooperation between exchange parties. When a party expects harmonious relationship with its partner, the party develops the relational norm through accepting short-term disadvantages that are expected to be balanced out by longer-term advantages. However, exchange parties with a low group-orientation culture do not rely on formal cooperation mechanisms

Correlation and Network Topologies in Global and Local Stock Indices

This study examined how the correlation and network structure of 30 global indices and 145 local Korean indices belonging to the KOSPI 200 have changed during the 13-year period, 2000-2012. The correlations among the indices were calculated. The results showed that although the average correlations of the global indices increased with time, the local indices showed a decreasing trend except for drastic changes during crises. The average correlation of the local indices exceeded the global indices during the crises from 2000-2002, implying a strong correlation structure among the local indices during this period due to the detrimental effect of the dot-com bubble. The threshold networks (TN) were constructed in the observation time window by assigning a threshold value and determining the network topologies. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities were also determined using the common links of TNs. The TNs of the financial network were not consistent with the evolution of the time, and the successive TNs of the global indices were more similar than those of the successive local indices. Finally, the Jaccard similarities identified the change in the market state due to a crisis in both markets.Comment: 11 pages,4 figure

Leveraging Spatio-Temporal Dependency for Skeleton-Based Action Recognition

Skeleton-based action recognition has attracted considerable attention due to its compact skeletal structure of the human body. Many recent methods have achieved remarkable performance using graph convolutional networks (GCNs) and convolutional neural networks (CNNs), which extract spatial and temporal features, respectively. Although spatial and temporal dependencies in the human skeleton have been explored, spatio-temporal dependency is rarely considered. In this paper, we propose the Inter-Frame Curve Network (IFC-Net) to effectively leverage the spatio-temporal dependency of the human skeleton. Our proposed network consists of two novel elements: 1) The Inter-Frame Curve (IFC) module; and 2) Dilated Graph Convolution (D-GC). The IFC module increases the spatio-temporal receptive field by identifying meaningful node connections between every adjacent frame and generating spatio-temporal curves based on the identified node connections. The D-GC allows the network to have a large spatial receptive field, which specifically focuses on the spatial domain. The kernels of D-GC are computed from the given adjacency matrices of the graph and reflect large receptive field in a way similar to the dilated CNNs. Our IFC-Net combines these two modules and achieves state-of-the-art performance on three skeleton-based action recognition benchmarks: NTU-RGB+D 60, NTU-RGB+D 120, and Northwestern-UCLA.Comment: 12 pages, 5 figure

Exploring the relationship between the spatial distribution of roads and universal pattern of travel-route efficiency in urban road networks

Urban road networks are well known to have universal characteristics and scale-invariant patterns, despite the different geographical and historical environments of cities. Previous studies on universal characteristics of the urban road networks mostly have paid attention to their network properties but often ignored the spatial networked structures. To fill the research gap, we explore the underlying spatial patterns of road networks. In doing so, we inspect the travel-route efficiency in a given road network across 70 global cities which provides information on the usage pattern and functionality of the road structure. The efficiency is quantified by the detour patterns of the travel routes, estimated by the detour index (DI). The DI is a long-standing popular measure, but its spatiality has been barely considered so far. In this study, we probe the behavior of DI with respect to spatial variables by scanning the network radially from a city center. Through empirical analysis, we first discover universal properties in DI throughout most cities, which are summarized as a constant behavior of DI regardless of the radial position from a city center and clear collapse into a single curve for DIs for various radii with respect to the angular distance. Especially, the latter enables us to know the scaling factor in the length scale. We also reveal that the core-periphery spatial structure of the roads induces the universal pattern, which is supported by an artificial road network model. Furthermore, we visualize the spatial DI pattern on the city map to figure out the city-specific characteristics. The most and least efficient connections of several representative cities show the potential for practical implications in analyzing individual cities.Comment: 11 pages, 6 figure