The challenging concern regarding how the benefits of inbound tourism can be evenly distributed, especially among urban and rural individuals, has received considerable attention in China. To address this concern, a spatial econometrics approach is used to estimate the spillover effects of inbound tourism on urban–rural income disparity (URID). An empirical analysis using the spatial Durbin model was conducted for 31 Chinese provinces covering the period from 2003 to 2017. Our findings suggest that at the national level, local inbound tourism significantly reduces the local URID, while neighboring inbound tourism significantly increases the local URID. At the regional level, the role of inbound tourism in reducing the local URID is only detected in the western region. The spillover effects of inbound tourism are positive and significant in the eastern/northeastern region but negative in the western region. In general, these findings provide insights into the importance of interregional tourism policies and strategies for inbound tourism development in China.
PurposeSharing of risk benefits supplies network collaborations. The complex mix of heterogeneous collaborators in supply networks, however, also increases the complexity of the risk profiles of inter‐related components within these networks. For a given network collaboration, several structures of network relationship are possible, with each carrying distinctive risk implications. This paper seeks to develop a conceptual framework for analysing the differential risks in alternative network structures.Design/methodology/approachTo capture the structural significance of inter‐organisational dependency in networks, alternative typology of network relationships is formulated using agency theory. Basic constructs were developed for analysing risks in supply networks, with configurations ranging from the single‐principal, single‐agent to the complex multi‐principal, multi‐agent scenarios.FindingsThe study finds that dynamics of risk in network systems depend not only on the typology of networks, but also on the functional role of each collaborator inherent in the network through agreements on supply and incentives, and supply performance.Originality/valueThe proposed framework provides a structured approach for identifying and assessing risk dynamics and their differential impacts on different levels of supply networks. It provides insights into the dynamics of risk events and identifies network configurations that are vulnerable to different levels of risk.
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