东南亚华人华侨网络与中国企业海外投资的区位选择关系研究

随着“走出去”战略的实施和“一带一路”倡议的提出,中国在全球化经济中逐渐成为国际投资的主要力量之一。海外华人华侨网络曾经积极促进外商对华的直接投资,是否在这个过程中再次扮演积极的作用,是当前经济地理领域尚未充分探究的问题。因此,本文从经典的区位选择问题切入,探究海外华人华侨网络与中国企业海外投资的区位选择的关系,利用2001-2016年中国企业投资东南亚国家的数据,通过混合逻辑模型回归分析海外华人华侨对中国企业投资区位的影响。结果表明：① 从整体上看,东南亚各国的华人华侨规模和中国企业对外直接投资的区位选择之间存在显著的正相关关系;② 从投资时间上看,海外华人华侨规模与中国企业对外直接投资区位选择之间的关系显著性呈现扩大趋势,说明华人华侨在促进中国企业对外投资方面存在较大潜力;③ 从投资的行业和环节上看,不同行业和不同职能部门的企业在东南亚投资中海外华人华侨在其投资区位选择中所起的作用不同。     

Economic‐Development Stakeholder Perspectives on Boomtown Dynamics in the Eagle Ford Shale,Texas

Unconventional oil and gas production in the United States reversed a decades‐old trend of rising oil imports, provided an argument for lifting the U.S. crude oil export ban and motivated the development of domestic natural gas export facilities. But the most visible impact of unconventional‐hydrocarbon extraction is the creation of boomtowns in rural regions. Despite widespread media coverage, scholarly analysis of boomtowns is restricted to regional econometric studies with little attention to how economic stakeholders understand and respond to booming economies. Here we analyze interviews with key economic stakeholders in the Eagle Ford Shale in Texas. Respondents consider their community's economic success relative to the price of oil and indicate concerns about the deterioration of roads, high housing demand, and skyrocketing wages. We also re‐examine John Gilmore's foundational work on boomtowns in the 1970s in the context of contemporary unconventional extraction.     

Rural Social Networks along Amazonian Rivers: Seeds,Labor and Soccer among Communities on the Napo River,Peru

Research on Amazonian communities has focussed more often on rural‐urban linkages than on links among rural communities. This is unsurprising, given the low density of population, limited intercommunity commerce, and importance of direct city‐market relations. Social relations among rural communities are also important in shaping rural livelihoods and lifeways. We report on the findings of a large‐scale census of communities in the Napo River basin in northeastern Peru (n=174). Data were gathered on intervillage crop seed acquisition and cooperative labor sharing as two key inputs in agriculture, and on intervillage soccer matches, which are integral to rural social life. We analyze the socio‐spatial networks of each practice, paying attention to settlement patterns, community ethnicity, and differential access to the uplands. We find that seeds and labor flow along soccer network lines. Rural social networks appear to be structured strongly by ethnicity (homophily) and reflect important complementarities between upland and lowland communities (weak ties).     

Mapping the Stakeholders: Using Social Network Analysis to Increase the Legitimacy and Transparency of Participatory Scenario Planning

Participatory scenario planning (PSP) processes rely on accurate stakeholder identification to develop a key set of critical uncertainties. While many stakeholder analysis methods are able to identify stakeholders and describe their relationships, we found these efforts to have limited use in the fast-moving and in-depth approach of PSP research. We find that social network analysis (SNA) is an efficient, objective, and transparent approach to stakeholder identification in highly contested natural resource management issues. We present a case study of our research on Alaska’s Kenai Peninsula to describe how SNA’s ability to contextualize the relations between actors can benefit participatory research.     

千岛湖旅游地聚居空间特征及其社会效应

作为新兴的重要发展力量,旅游正在不可逆转地改变着聚居空间演变进程。旅游地聚居空间特征及其社会效应是透视旅游地社会转型的重要维度之一,旅游地聚居现象已构成旅游地理学研究的重要命题。以千岛湖为案例,立足社区尺度,应用实地观察法、访谈法、问卷调查方法、GIS空间技术、统计分析法,探究千岛湖旅游地聚居空间发展过程;识别和划分居住社区类型,测算居住社区空间分异度,揭示旅游影响下典型聚居区分布格局;从居住满意度、社会交往和社会融合三个方面,构建聚居空间社会效应指标体系。研究发现：① 伴随着社会经济转型、旅游产业发展与城市更新的不断推进,千岛湖镇聚居空间发展经历了5个发展阶段。② 识别了76个基本空间单元,将76个居住小区划分为乡村社区、商住混合社区、老旧住房社区、一般商品房社区、高档商品房社区、高档别墅区、旅游度假社区7种类型。③ 城市居住空间分异现象存在于旅游地聚居空间。社会阶层越低的社区居住分异度越大,社会阶层较高的社区居住分异度越小。千岛湖镇聚居空间呈现圈层结构分布模式,从湖岸到中心城区,居住等级逐渐降低,乡村社区呈扇型镶嵌于主城区居住空间结构上,老旧住房社区和旅游度假社区分布于千岛湖镇外围。④ 旅游发展导致了聚居空间社会分异,引致旅游地传统社会关系的裂变分化,进一步影响聚居满意度、社会交往和社会融合。千岛湖镇旅游地社区居住总体处于较满意状态,且千岛湖镇社区居住满意度存在明显的空间差异,不同社区个体交友意愿存在差异,大部分居民能较好地适应本地生活。     

基于倾向值匹配法的城市建成环境对居民生理健康的影响

伴随着城市化和机动化进程,肥胖及其引致的慢性疾病已成为中国严峻的社会问题。本文利用2010年中国社会综合调查、空间兴趣点POI、道路网等数据,探究城市建成环境对居民生理健康状况的影响,并通过倾向值匹配法控制自选择机制的干扰。研究发现：① 高密度的土地利用对居民总体的身体健康状况具有负向影响,而功能混合、支路网通达的城市肌理、以及充足的健康设施在降低身体质量指数BMI、抑制超重和减少慢性病方面发挥着积极作用。② 各类建成环境特征对中高社会阶层的影响集中在主观的健康感知,对中低阶层人群的影响则主要作用于客观的健康指标。③ 小尺度范围内的建成环境与中低阶层群体的身体健康水平存在更为密切的关联,但这一规律在中高社会阶层并不明显。本研究证明了主动式空间干预手段在促进居民生理健康过程中的有效性,进而就建成环境的优化策略提出了初步建议。     

The progress of human geography in China under the support of the National Natural Science Foundation of China

This paper analyzes the role of the National Natural Science Foundation of China (NSFC) in advancing human geography in China by focusing on five key research areas: land use, urban systems and urban agglomeration, economic globalization, climate change and social and cultural geographies. All NSFC-funded human geography programs related to these five topics from 1986 to 2017 comprise the sample for analysis, and the research topics, content, teams, and peer-reviewed journal publications supported by these programs are investigated. Specifically, this paper analyzes the NSFC’s promotion of the expansion of research topics in response to national developmental needs and the shifting frontiers of human geography research internationally, its enhancement of interdisciplinary research, and its contributions to the assembly of specialized research teams. The paper also reports important progress in Chinese human geography over the past 30 years through the institutional lens of the NSFC, revealing major characteristics and trends in the discipline. The paper concludes by calling for further collaboration between the research community and the NSFC for the development of a locally suitable and globally influential Chinese human geography.     

Pesticide-related Food Safety Risks: Farmers’ Self-protective Behavior and Food Safety Social Co-governance

This article investigates the sources of vegetables consumed by farmers, their perception of pesticide-related food safety risks and the behaviors they engage in to protect themselves, and explores the implications for the social co-governance (shehui gongzhi) of food safety emphasized by China’s recent Food Safety Law. The research site is a county in Yunnan Province where vegetable growing is the major source of income and livelihood for local farmers. We surveyed 417 farmers and collected 776 vegetable samples from 377 surveyed farmer households and tested them for organophosphate and carbamate pesticide residues using PR-12N Rapid Detection Instrument for Pesticide Residues. The results showed that farmers know about the risks to food safety caused by pesticides used in vegetable growing and they purposely avoid these risks by mainly consuming vegetables planted in home gardens or private plots that use little or no pesticides. Vegetable samples from these private plots had the lowest positive rate of pesticide residues (6.10%), compared with vegetable samples from commercial farmland (13.73%) and markets (12.66%), and the difference was statistically significant (X²=9.69,0.005相似文献   

Classifying urban land use by integrating remote sensing and social media data

Urban land use information plays an important role in urban management, government policy-making, and population activity monitoring. However, the accurate classification of urban functional zones is challenging due to the complexity of urban systems. Many studies have focused on urban land use classification by considering features that are extracted from either high spatial resolution (HSR) remote sensing images or social media data, but few studies consider both features due to the lack of available models. In our study, we propose a novel scene classification framework to identify dominant urban land use type at the level of traffic analysis zone by integrating probabilistic topic models and support vector machine. A land use word dictionary inside the framework was built by fusing natural–physical features from HSR images and socioeconomic semantic features from multisource social media data. In addition to comparing with manual interpretation data, we designed several experiments to test the land use classification accuracy of our proposed model with different combinations of previously acquired semantic features. The classification results (overall accuracy = 0.865, Kappa = 0.828) demonstrate the effectiveness of our strategy that blends features extracted from multisource geospatial data as semantic features to train the classification model. This method can be applied to help urban planners analyze fine urban structures and monitor urban land use changes, and additional data from multiple sources will be blended into this proposed framework in the future.     

Classifying natural-language spatial relation terms with random forest algorithm

The exponential growth of natural language text data in social media has contributed a rich data source for geographic information. However, incorporating such data source for GIS analysis faces tremendous challenges as existing GIS data tend to be geometry based while natural language text data tend to rely on natural language spatial relation (NLSR) terms. To alleviate this problem, one critical step is to translate geometric configurations into NLSR terms, but existing methods to date (e.g. mean value or decision tree algorithm) are insufficient to obtain a precise translation. This study addresses this issue by adopting the random forest (RF) algorithm to automatically learn a robust mapping model from a large number of samples and to evaluate the importance of each variable for each NLSR term. Because the semantic similarity of the collected terms reduces the classification accuracy, different grouping schemes of NLSR terms are used, with their influences on classification results being evaluated. The experiment results demonstrate that the learned model can accurately transform geometric configurations into NLSR terms, and that recognizing different groups of terms require different sets of variables. More importantly, the results of variable importance evaluation indicate that the importance of topology types determined by the 9-intersection model is weaker than metric variables in defining NLSR terms, which contrasts to the assertion of ‘topology matters, metric refines’ in existing studies.