Agent-Based Modeling of Spatial Spillover Effects in Visitor Flows

In this study, we apply an agent-based modeling approach to understand individual visitors’ multidestination travel patterns and the spatial spillover effects in visitor flows as an aggregate outcome. Based on previous literature, we specify three hypothetic visitor categories (global optimizers, sequential optimizers, and radial optimizers) according to visitors’ attraction selection rules. We conduct an ABM simulation with a sample of 341 Chinese cities as destinations and 1,990 attractions to measure the degree of spillover between destinations by observing the frequency with which visitors traveling across destination boundaries visited attractions in other destinations. The simulation results demonstrate slightly different spillover effects based on visitor type and highlight three regions with particularly strong spillover effects: the Bohai Rim region, the Yangtze River Delta region, and the Sichuan and Chongqing region. These results appear consistent with those of exploratory spatial data analysis in a validation check. Lastly, policy implications are provided.

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Spatial spillover effects of urbanization on carbon emissions in the Yangtze River Delta urban agglomeration, China

Environmental Science and Pollution Research ◽

10.1007/s11356-021-17872-x ◽

2022 ◽

Author(s):

Tiangui Lv ◽

Han Hu ◽

Xinmin Zhang ◽

Hualin Xie ◽

Li Wang ◽

...

Keyword(s):

Carbon Emissions ◽

Yangtze River ◽

Spillover Effects ◽

Yangtze River Delta ◽

River Delta ◽

Urban Agglomeration ◽

The Yangtze River ◽

Spatial Spillover ◽

Spatial Spillover Effects ◽

The Yangtze River Delta

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Do Transportation Infrastructure Investments Reduce Inventory Levels in the Manufacturing Sector in China?

International Regional Science Review ◽

10.1177/0160017619849632 ◽

2019 ◽

Vol 43 (4) ◽

pp. 397-420

Author(s):

Ya Lin ◽

Quanwu Zhao ◽

Peisen Liu ◽

Qinhong Zhang

Keyword(s):

Manufacturing Sector ◽

Spillover Effects ◽

Transportation Infrastructure ◽

Policy Implications ◽

Spatial Spillover ◽

Positive Effects ◽

Market Expansion ◽

Spatial Spillover Effects ◽

The Difference ◽

Infrastructure Investments

Based on provincial panel data observed over the 2005–2014 period, we analyze the impacts of transportation infrastructure investments on inventory levels in China’s manufacturing sector. Our results indicate that transportation infrastructure investments do not reduce inventory levels in the manufacturing sector in China. This conclusion is different from the results in the previous literature, which demonstrate positive effects of transportation investments on reducing inventory levels. The difference can be partly explained by the ongoing inland shift of industry and geographic market expansion in China, which lead to longer transportation distances and longer lead times from suppliers to customers. We also find that road investments have spatial spillover effects overall, and the impacts of different types of road investments differ significantly from each other. Railway investments, however, do not have spatial spillover effects. Finally, we present several policy implications of transportation infrastructure investments, inland shifts of industry, and geographic market expansion.

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Spatiotemporal Evolution and Influencing Factors of Carbon Sink Dynamics at County Scale: A Case Study of Shaanxi Province, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182413081 ◽

2021 ◽

Vol 18 (24) ◽

pp. 13081

Author(s):

Shuohua Liu ◽

Xiao Zhang ◽

Yifan Zhou ◽

Shunbo Yao

Keyword(s):

Local Government ◽

Fixed Effects ◽

Carbon Sink ◽

Spillover Effects ◽

Spatial Data Analysis ◽

Shaanxi Province ◽

Carbon Sinks ◽

Spatiotemporal Evolution ◽

Spatial Spillover ◽

Spatial Spillover Effects

To explore the spatiotemporal evolution of carbon sinks in Shaanxi Province, and their impact mechanisms, this study used panel data from 107 counties (districts) in Shaanxi Province from 2000 to 2017. First, we conducted spatial distribution directional analysis and exploratory spatial data analysis (ESDA). Then, we constructed a geographic spatial weight matrix and used the spatial panel Durbin model to analyze the driving factors of carbon sink changes in Shaanxi Province, from the perspective of spatial effects. The results showed that: (1) The temporal evolution of carbon sinks during the study period showed an overall upward trend, but the carbon sinks of counties (districts) differed greatly, and the center of gravity of carbon sinks, as a whole, showed the characteristics of “south to north” migration. (2) The carbon sinks of Shaanxi Province have a significant positive global spatial autocorrelation in geographic space. The local spatial pattern was characterized by low-value agglomeration (low-low cluster) and high-value agglomeration (high-high cluster), supplemented by high-value bulge (high-low outlier) and low-value collapse (low-high outlier). (3) The result of the spatial measurement model proved that the spatial Durbin model, with dual fixed effects of time and space, should be selected. In the model results, factors such as population, per capita gross domestic product (GDP), local government general budget expenditure, and local government general budget revenue all reflect strong spatial spillover effects. Accordingly, in the process of promoting “carbon neutrality”, the government needs to comprehensively consider the existence of spatial spillover effects between neighboring counties (districts), and strengthen the linkage-management and control roles of counties (districts) in increasing carbon sinks.

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Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

Tourism Economics ◽

10.1177/13548166211021175 ◽

2021 ◽

pp. 135481662110211

Author(s):

Honghong Liu ◽

Ye Xiao ◽

Bin Wang ◽

Dianting Wu

Keyword(s):

Economic Growth ◽

Spillover Effect ◽

Tourism Development ◽

Spillover Effects ◽

Policy Implications ◽

Long Term Effects ◽

Spatial Spillover ◽

Domestic Tourism ◽

Inbound Tourism ◽

Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

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