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2024年 第34卷  第2期

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Innovation and Firm Co-ownership Network in China’s Electric Vehicle Industry
Zerun JIN, Shengjun ZHU
2024, 34(2): 195-209. doi: 10.1007/s11769-023-1403-8
摘要:
Firms are embedded in complex networks, where diverse ideas combine and generate new ideas. Shareholders of firms are often seen as critical external resources that have significant influence on firm innovation. The current literature tends to focus on the relationship between firms and their shareholders, while paying less attention to the connections between firms with the same shareholders. This article identifies two types of network spillover effects, intra-city network effect and inter-city network effect, by visualizing the co-ownership networks in China’s electric vehicle (EV) industry. We find that firms with the same shareholders, which are defined as co-owned EV firms, are more innovative than non-co-owned ones. Furthermore, there are two dominant types of firm co-ownership ties formed by corporate and financial institution shareholders. While corporate shareholders help exploiting local tacit knowledge, financial institutions are more active in bridging inter-city connections. The conclusion is confirmed at both firm and city levels. This paper theorizes the firm co-ownership network as a new form of institutional proximity and tested the result empirically. For policy consideration, we have emphasized the importance of building formal or informal inter-firm network, and the government should further enhance the knowledge flow channel by institutional construction.
Industrial Carbon Emission Distribution and Regional Joint Emission Reduction: A Case Study of Cities in the Pearl River Basin, China
Hongtao JIANG, Jian YIN, Bin ZHANG, Danqi WEI, Xinyuan LUO, Yi DING, Ruici XIA
2024, 34(2): 210-229. doi: 10.1007/s11769-024-1416-y
摘要:
China’s low-carbon development path will make significant contributions to achieving global sustainable development goals. Due to the diverse natural and economic conditions across different regions in China, there exists an imbalance in the distribution of carbon emissions. Therefore, regional cooperation serves as an effective means to attain low-carbon development. This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intensity (ICEI) as a crucial factor. We utilized social network analysis and Local Indicators of Spatial Association (LISA) space-time transition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin (PRB), China from 2010 to 2020. The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression. The results were as follows: 1) the overall ICEI in the Pearl River Basin is showing a downward trend, and there is a significant spatial imbalance. 2) There are numerous network connections between cities regarding the ICEI, but the network structure is relatively fragile and unstable. 3) Economically developed cities such as Guangzhou, Foshan, and Dongguan are in the center of the network while playing an intermediary role. 4) Energy consumption, industrialization, per capita GDP, urbanization, science and technology, and productivity are found to be the most influential variables in the spatial differentiation of ICEI, and their combination increased the explanatory power of the geographic variation of ICEI. Finally, through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI, the study suggests joint carbon reduction strategies, which are centered on carbon transfer, financial support, and technological assistance among cities.
Spatial Differentiation and Convergence Trend of High-quality Development Level of China’s Tourism Economy
Shanshan CAO, Zhaoli HE, Jinlan NIU, Songmao WANG, Lei ZHAO
2024, 34(2): 230-249. doi: 10.1007/s11769-024-1413-1
摘要:
This paper aims to interpret the connotation of high-quality development of tourism economy (HQTE) from the perspective of the new development concepts of innovation, coordination, green, openness and sharing, and then to evaluate the spatial differentiation of China’s HQTE based on provincial panel data from 2009 to 2018. Specifically, we employ the spatial convergence model to explore the absolute and conditional β convergence trends of HQTE in the whole country and the eastern, central and western regions of China. Our empirical results reveal that: 1) within the decade, from 2009 to 2018, regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region, but the fastest growing one is the western region of China followed by the central region and then the eastern region. 2) Whether or not the spatial effect is included, there are absolute and conditional β convergence in HQTE in the whole country and aforementioned three regions. 3) The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions. The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions. The above conclusions could deepen the understanding of the regional imbalance and spatial convergence characteristics of HQTE, clarify the primary development objects, and accomplish the goal of China’s HQTE.
Global Research Progress on Municipal Waste and Future Prospect Based on the Cross-national Comparisons
Yuxin ZHANG, Xiaoqian LIU, Xiaoxia YAN, Sike MA, Weiyun MAO
2024, 34(2): 250-264. doi: 10.1007/s11769-023-1396-3
摘要:
Due to the acceleration of urbanization, the municipal waste (MW) problem has transformed into a global challenge for urban sustainability. To elucidate historical trends, current focal points, and future directions in MW research, we conducted a bibliometric analysis and employed knowledge graph visualization to scrutinize a total of 34 212 articles, which were published between 1991 and 2021 in the Web of Science (WoS) core database. The results indicated that current major research themes encompass waste classification and recycling, waste management and public behavior, waste disposal methods and technologies, as well as environmental impact and evaluation. There has been a shift in the research focus from the environmental impacts of waste incineration to sustainable management related issues. A comparison of research from six typical countries revealed the differences in research priorities and techniques advantages. Scholars from the USA and Britain initiated MW research earlier than other countries and investigated management issues in depth, such as public behavior and willingness to pay. Meanwhile, Japanese, German, and Swedish scholars conducted extensive studies on advanced waste treatment technologies, such as disposal and recycling, risk assessment, and waste-to-energy techniques. Chinese scholars placed particular emphasis on end-of-pipe treatments and their associated environmental impacts. Hotspots and potential future frontiers were identified by burst detection analysis. Keywords with high value of burst index (BI) worldwide are food waste and circular economy. Chinese scholars have put great efforts on waste environmental impact and its recycling technologies, while we’re expecting to further investigating vulnerable population. Furthermore, this study contributes to bridging the regional gap of scientific research among different countries and fostering international collaboration.
Changes of China’s Status in the Global System and Its Influencing Factors: A Multiple Contact Networks Perspective
Jian LIU, Jibin LIU, Qingshan YANG, Sikai CAI, Jie LIU
2024, 34(2): 265-279. doi: 10.1007/s11769-024-1419-8
摘要:
Clarifying China’s position in the global system is an important logical basis for developing national diplomacy. Although much research has been done on China’s development status, most studies have been based on country comparisons or institutional environment. In today’s networked era in which the global economy, trade, personnel, and information are closely connected, studies on China’s global position and its status changes and influencing factors in multiple contact networks are still insufficient. In this study, from the perspective of diverse global contact networks, we constructed economic, cultural, and political influence indices to explore the changes and influencing factors on China’s status in the global system from 2005 to 2018. The results show that during the study period, China’s global influence in the fields of economic ties, cultural exchanges, and political contacts increased significantly, but its influence in the fields of cultural exchanges and political contacts lagged far economic ties. The pattern of China’s economic influence on various economies around the world has shown a transformation from an ‘upright pyramid’ to an ‘inverted pyramid’ structure. The proportion of these economies in low-influence zones has decreased from more than 60% in 2005 to less than 20% in 2018. China’s cultural and political influence on various economies around the world has increased significantly; however, for the former, the percentage of high-influence areas is still less than 20%, whereas for the latter the percentage of these economies in medium- and high-influence areas is still less than 50%. Analyses such as a scatter plot matrix show that geographical proximity, economic globalization, close cooperation with developing countries, and a proactive and peaceful foreign policy are important factors in improving China’s status in the diverse global network system.
Centennial Analysis of Human Activity Intensity and Associated Historical Events in Heilongjiang River Sino-Russo Watershed
Chaoxue SONG, Xiaoling LI, Hongshi HE, SUNDE Michael
2024, 34(2): 280-293. doi: 10.1007/s11769-023-1401-x
摘要:
Human activities in a transborder watershed are complex under the influence of domestic policies, international relations, and global events. Understanding the forces driving human activity change is important for the development of transborder watershed. In this study, we used global historical land cover data, the hemeroby index model, and synthesized major historical events to analyze how human activity intensity changed in the Heilongjiang River (Amur River in Russia) watershed (HLRW). The results showed that there was a strong spatial heterogeneity in the variation of human activity intensity in the HLRW over the past century (1900–2016). On the Chinese side, the human activity intensity change shifted from the plain areas for agricultural reclamation to the mountainous areas for timber extraction. On the Russian side, human activity intensity changes mostly concentrated along the Trans-Siberian Railway and the Baikal-Amur Mainline. Localized variation of human activity intensity tended to respond to regional events while regionalized variation tends to reflect national policy change or broad international events. The similarities and differences between China and Russia in policies and positions in international events resulted in synchronous and asynchronous changes in human activity intensity. Meanwhile, policy shifts were often confined by the natural features of the watershed. These results reveal the historical origins and fundamental connotations of watershed development and contribute to formulating regional management policies that coordinate population, economic, social, and environmental activities.
Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6
Ziyue XU, Kai MA, Xu YUAN, Daming HE
2024, 34(2): 294-310. doi: 10.1007/s11769-024-1420-2
摘要:
Within the context of the Belt and Road Initiative (BRI) and the China-Myanmar Economic Corridor (CMEC), the Dulong-Irrawaddy (Ayeyarwady) River, an international river among China, India and Myanmar, plays a significant role as both a valuable hydropower resource and an essential ecological passageway. However, the water resources and security exhibit a high degree of vulnerability to climate change impacts. This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin (DIRB) by using a physical-based hydrologic model. We crafted future climate scenarios using the three latest global climate models (GCMs) from Coupled Model Intercomparison Project 6 (CMIP6) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) for the near (2025–2049), mid (2050–2074), and far future (2075–2099). The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow, demonstrating reliable performance in streamflow simulations with a validation Nash-Sutcliffe Efficiency (NSE) of 0.72. Results showed that climate change projections showed increases in the annual precipitation and potential evapotranspiration (PET), with precipitation increasing by 11.3% and 26.1%, and PET increasing by 3.2% and 4.9%, respectively, by the end of the century under SSP2-4.5 and SSP5-8.5. These changes are projected to result in increased annual streamflow at all stations, notably at the basin’s outlet (Pyay station) compared to the baseline period (with an increase of 16.1% and 37.0% at the end of the 21st century under SSP2-4.5 and SSP5-8.5, respectively). Seasonal analysis for Pyay station forecasts an increase in dry-season streamflow by 31.3%–48.9% and 22.5%–76.3% under SSP2-4.5 and SSP5-8.5, respectively, and an increase in wet-season streamflow by 5.8%–12.6% and 2.8%–33.3%, respectively. Moreover, the magnitude and frequency of flood events are predicted to escalate, potentially impacting hydropower production and food security significantly. This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.
Spatial Heterogeneity of Embedded Water Consumption from the Perspective of Virtual Water Surplus and Deficit in the Yellow River Basin, China
Weijing MA, Xiangjie LI, Jingwen KOU, Chengyi LI
2024, 34(2): 311-326. doi: 10.1007/s11769-024-1415-z
摘要:
Virtual water trade (VWT) provides a new perspective for alleviating water crisis and has thus attracted widespread attention. However, the heterogeneity of virtual water trade inside and outside the river basin and its influencing factors remains further study. In this study, for better investigating the pattern and heterogeneity of virtual water trade inside and outside provincial regions along the Yellow River Basin in 2015 using the input-output model (MRIO), we proposed two new concepts, i.e., virtual water surplus and virtual water deficit, and then used the Logarithmic Mean Divisia Index (LMDI) model to identify the inherent mechanism of the imbalance of virtual water trade between provincial regions along the Yellow River Basin and the other four regions in China. The results show that: 1) in provincial regions along the Yellow River Basin, the less developed the economy was, the larger the contribution of the agricultural sector in virtual water trade, while the smaller the contribution of the industrial sector. 2) Due to the large output of agricultural products, the upstream and midstream provincial regions of the Yellow River Basin had a virtual water surplus, with a net outflow of virtual water of 2.7 × 108 m3 and 0.9 × 108 m3, respectively. 3) provincial regions along the Yellow River Basin were in a virtual water deficit with the rest of China, and the decisive factor was the active degree of trade with the outside. This study would be beneficial to illuminate the trade-related water use issues in provincial regions along the Yellow River Basin, which has far-reaching practical significance for alleviating water scarcity.
Migration Networks Pattern of China’s Floating Population from the Perspective of Complex Network
Wangbao LIU, Ranran CHEN
2024, 34(2): 327-341. doi: 10.1007/s11769-023-1402-9
摘要:
Since China’s reform and opening-up, the growing disparity between urban and rural areas and regions has led to massive migration. With China’s Rural Revitalization Strategy and the industrial transfer from the eastern coastal areas to the inland, the migration direction and pattern of the floating population have undergone certain changes. Using the 2017 China Migrants Dynamic Survey (CMDS), excluding Hong Kong, Macao, and Taiwan regions of China, organized by China’s National Health Commission, the relationship matrix of the floating population is constructed according to the inflow place of the interviewees and their outflow place (the location of the registered residence) in the questionnaire survey. We then apply the complex network model to analyze the migration direction and network pattern of China’s floating population from the city scale. The migration network shows an obvious hierarchical agglomeration. The first-, second-, third- and fourth-tier distribution cities are municipalities directly under the central government, provincial capital cities, major cities in the central and western regions and ordinary cities in all provinces, respectively. The migration trend is from the central and western regions to the eastern coastal areas. The migration network has ‘small world’ characteristics, forming nine communities. It shows that most node cities in the same community are closely linked and geographically close, indicating that the migration network of floating population is still affected by geographical proximity. Narrowing the urban-rural and regional differences will promote the rational distribution this population. It is necessary to strengthen the reform of the registered residence system, so that the floating population can enjoy urban public services comparable to other populations, and allow migrants to live and work in peace.
Winter Wheat Yield Estimation Based on Sparrow Search Algorithm Combined with Random Forest: A Case Study in Henan Province, China
Xiaoliang SHI, Jiajun CHEN, Hao DING, Yuanqi YANG, Yan ZHANG
2024, 34(2): 342-356. doi: 10.1007/s11769-024-1421-1
摘要:
Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies. However, crop yield is influenced by multiple factors within complex growth environments. Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat. Therefore, there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield, making precise yield prediction increasingly important. This study was based on four type of indicators including meteorological, crop growth status, environmental, and drought index, from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield. Using the sparrow search algorithm combined with random forest (SSA-RF) under different input indicators, accuracy of winter wheat yield estimation was calculated. The estimation accuracy of SSA-RF was compared with partial least squares regression (PLSR), extreme gradient boosting (XGBoost), and random forest (RF) models. Finally, the determined optimal yield estimation method was used to predict winter wheat yield in three typical years. Following are the findings: 1) the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms. The best yield estimation method is achieved by four types indicators’ composition with SSA-RF) (R2 = 0.805, RRMSE = 9.9%. 2) Crops growth status and environmental indicators play significant roles in wheat yield estimation, accounting for 46% and 22% of the yield importance among all indicators, respectively. 3) Selecting indicators from October to April of the following year yielded the highest accuracy in winter wheat yield estimation, with an R2 of 0.826 and an RMSE of 9.0%. Yield estimates can be completed two months before the winter wheat harvest in June. 4) The predicted performance will be slightly affected by severe drought. Compared with severe drought year (2011) (R2 = 0.680) and normal year (2017) (R2 = 0.790), the SSA-RF model has higher prediction accuracy for wet year (2018) (R2 = 0.820). This study could provide an innovative approach for remote sensing estimation of winter wheat yield. yield.
Spatiotemporal Changes of Snow Depth in Western Jilin, China from 1987 to 2018
Yanlin WEI, Xiaofeng LI, Lingjia GU, Zhaojun ZHENG, Xingming ZHENG, Tao JIANG
2024, 34(2): 357-368. doi: 10.1007/s11769-023-1400-y
摘要:
Seasonal snow cover is a key global climate and hydrological system component drawing considerable attention due to global warming conditions. However, the spatiotemporal snow cover patterns are challenging in western Jilin, China due to natural conditions and sparse observation. Hence, this study investigated the spatiotemporal patterns of snow cover using fine-resolution passive microwave (PMW) snow depth (SD) data from 1987 to 2018, and revealed the potential influence of climate factors on SD variations. The results indicated that the interannual range of SD was between 2.90 cm and 9.60 cm during the snowy winter seasons and the annual mean SD showed a slightly increasing trend (P > 0.05) at a rate of 0.009 cm/yr. In snowmelt periods, the snow cover contributed to an increase in volumetric soil water, and the change in SD was significantly affected by air temperature. The correlation between SD and air temperature was negative, while the correlation between SD and precipitation was positive during December and March. In March, the correlation coefficient exceeded 0.5 in Zhenlai, Da’an, Qianan, and Qianguo counties. However, the SD and precipitation were negatively correlated over western Jilin in October, and several subregions presented a negative correlation between SD and precipitation in November and April.
Relationship Between Individuals’ Epidemic Risk Perception Within Living Space and Subjective Well-Being: Empirical Evidence from China after the First Wave of COVID-19
Jiangyu SONG, Suhong ZHOU, Mei-Po KWAN, Zhong ZHENG
2024, 34(2): 369-382. doi: 10.1007/s11769-024-1414-0
摘要:
It is common to observe the epidemic risk perception (ERP) and a decline in subjective well-being (SWB) in the context of public health events, such as Corona Virus Disease 2019 (COVID-19). However, there have been few studies exploring the impact of individuals’ ERP within living space on their SWB, especially from a geographical and daily activity perspective after the resumption of work and other activities following a wave of the pandemic. In this paper, we conducted a study with 789 participants in urban China, measuring their ERP within living space and examining its influence on their SWB using path analysis. The results indicated that individuals’ ERP within their living space had a significant negative effect on their SWB. The density of certain types of facilities within their living space, such as bus stops, subway stations, restaurants, fast food shops, convenience shops, hospitals, and public toilets, had a significantly negative impact on their SWB, mediated by their ERP within living space. Additionally, participation in out-of-home work and other activities not only increased individuals’ ERP within living space, but also strengthened its negative effect on their SWB.