自然资源依赖对城乡收入差距的影响研究

［目的］针对全国31个省（市、区）（不含港澳台地区）、自然资源依赖度高的地区和自然资源依赖度低的地区，从整体和分区域研究自然资源依赖对城乡收入差距的影响，探究不同区域其影响程度的差异性，进而为弱化各区域城乡收入差距，解决由城乡收入差距拉大造成的各类社会矛盾具有重要的现实意义。［方法］从理论上分析了自然资源依赖对城乡收入差距的影响，并利用1999—2017年的省级面板数据，运用固定效应模型，从全国和分区域实证分析了自然资源依赖对城乡收入差距的影响。［结果］针对全国，自然资源依赖会拉大城乡收入差距； 分区域结果，针对自然资源依赖度高的地区，自然资源依赖拉大城乡收入差距； 针对自然资源依赖度低的地区，自然资源依赖对城乡收入差距影响不显著。［结论］为缩小城乡收入差距，需要降低经济体对自然资源的依赖，针对自然资源依赖度高的地区，政府通过将部分自然资源收益转化为农业创新基金和农村基础设施投入，促进自然资源收益向农村公共资本转化，完善现有的自然资源收益分配及转化制度； 鼓励资源型产业技术创新，加大研发投入，延长资源产业链； 加大农村教育投入、提升农村人力资本质量。     

全球价值链下中国增加值贸易的核算及网络特征研究

基于投入产出模型和社会网络分析，利用世界投入产出表相关数据，对2000—2014年中国的增加值贸易进行核算，并分析全球增加值贸易的网络特征。研究结果显示：（1）从出口目的地来看，中国向美国、日本、德国等国家的增加值出口较大；（2）从行业来看，中国的纺织业、除汽车和摩托车之外的其他产品批发业、采矿业等行业的增加值出口较大；（3）根据网络密度的计算结果，世界范围的各国（地区）贸易联系程度在增强；（4）中国的相对点度数和点强度有上升的趋势，而日本和美国有下降的趋势，说明中国在世界增加值贸易格局中的地位在提升，不过美国仍在世界增加值贸易格局中占据主导地位；（5）核心边缘分析结果表明核心国家（地区）的数目经历了先增加后减少的过程，边缘国家（地区）数目则先减少后增加。其中，中国的核心度一直在增加，日本和美国的核心度呈现下降的趋势。因此，为了扩大增加值贸易，增强国际贸易的话语权，中国政府有必要采取调整进出口税率等政策，并重视与美国等国家的双边贸易合作，以实现双赢的结果。     

平顶山市休闲农业不同区域的发展潜力评价

[目的]对平顶山市休闲农业的空间分布特征及其发展潜力进行分析和评价,以期为平顶山市休闲农业的可持续发展提供参考和借鉴。[方法]文章对平顶山市休闲农业空间布局分区论述,并采用层次分析法构建平顶山市休闲农业发展潜力指标评价体系,确定指标权重,然后根据各指标的游客和当地农民的打分值与权重值加权计算不同区域的发展潜力指数并比较发展潜力大小。[结果]根据区域位置和地理环境以及休闲农业发展速度,将平顶山市休闲农业划分为北部山区休闲农业区、东部城乡休闲农业区、南部现代休闲农业区和西部傍水休闲农业区4个区域,各区域发展特点突出。对各指标权重值与打分值的加权求和计算得到的不同区域发展潜力指数看出,西部傍水休闲农业区的发展潜力最大,其次为北部山区休闲农业区,再者是南部现代休闲农业区,东部城郊休闲农业区的发展潜力最小。[结论]平顶山市休闲农业发展前景广阔,具有可持续发展的巨大潜力。由于地理区位和交通基础设施建设及环境条件和农业基础的差异,平顶山市的休闲农业可分为东西南北4个发展区域,其中西部傍水休闲农业区和北部山区休闲农业区具有较大的发展潜力,平顶山市可将其作为重点发展对象,重点打造水岸和山村休闲农业游,借助发展优势突出区域特色。     

Do ongoing networks block out new friends? Reconciling the embeddedness constraint dilemma on new alliance partner addition

Research Summary: This study addresses a theoretical dilemma regarding how alliance network constraint (reflected by network cohesion) affects a firm’s alliance formation with new partners. Using a network pluralism approach, we separate a firm’s ego alliance network into two activity‐based networks—an exploratory network and an exploitative network—based on the primary value chain activity involved in each alliance. We argue that the cohesion of exploratory or exploitative networks has an inverted U‐shaped effect on the addition of new partners in the same activity‐based network, and a positive effect on the addition of new partners in the other network. Results based on data from the biotechnology industry largely support our predictions with one exception. Our study contributes to both scholarly understanding of network embeddedness and alliance practice. Managerial Summary: The structure of firms’ ongoing alliance networks may have paradoxical implications for their efforts to search for and form alliance with new partners. That is, when a firm’s alliance partners are tightly connected with each other, the cohesive network tends to both encourage and impede the focal firm to add new partners. We resolve this dilemma by showing that when a firm is deeply entrenched in a cohesive alliance network conducting a certain type of activities (e.g., R&D activities), it may not easily add new R&D alliance partners. However, it may still be able to escape from the cohesive R&D alliance network by seeking new partners conducting other activities (e.g., manufacturing activities).     

The problem of employees' network centrality and supervisors' error in performance appraisal: A multilevel theory

This article reveals an unexplored paradox for HR managers: the centrality of an employee in the social network benefits performance but hampers performance appraisal because it affects supervisors' rating errors. Central employees can be erroneously rated high on performance even when they are not high performers because supervisors tend to overappraise their performance. A distinction is made between rating precision, which depends on supervisors' uncertainty regarding employees' performance, and rating accuracy, which depends on supervisors' bias in favor of employees. Employee centrality is posited to be beneficial to precision but deleterious to accuracy because it regulates the diffusion of positive information, status, and power, all of which distort supervisors' capacity and motivation to accurately appraise performance. It is then argued that rating errors caused by network centrality affect aggregate perceptions of justice in organizations. When employees are highly connected to each other in a dense network, organizations have a strong and positive justice climate. Yet when some employees are more central than others in a centralized network, organizations have a negative and weak justice climate. The article contributes to the literature because it identifies an unexplored dark side of network centrality and offers recommendations for HR managers to cope with its deleterious consequences and for scholars to study them.     

Conditional risk measures in a bipartite market structure

In this paper, we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the financial or (re)insurance market by a bipartite graph. Using Pareto-tailed losses and multivariate regular variation, we obtain asymptotic results for conditional risk measures based on the Value-at-Risk and the Conditional Tail Expectation. These results allow us to assess the influence of an individual institution on the systemic or market risk and vice versa through a collection of conditional risk measures. For large markets, Poisson approximations of the relevant constants are provided. Differences of the conditional risk measures for an underlying homogeneous and inhomogeneous random graph are illustrated by simulations.     

A gossip based information fusion protocol for distributed frequent itemset mining

The computational complexity, huge memory space requirement, and time-consuming nature of frequent pattern mining process are the most important motivations for distribution and parallelization of this mining process. On the other hand, the emergence of distributed computational and operational environments, which causes the production and maintenance of data on different distributed data sources, makes the parallelization and distribution of the knowledge discovery process inevitable. In this paper, a gossip based distributed itemset mining (GDIM) algorithm is proposed to extract frequent itemsets, which are special types of frequent patterns, in a wireless sensor network environment. In this algorithm, local frequent itemsets of each sensor are extracted using a bit-wise horizontal approach (LHPM) from the nodes which are clustered using a leach-based protocol. Heads of clusters exploit a gossip based protocol in order to communicate each other to find the patterns which their global support is equal to or more than the specified support threshold. Experimental results show that the proposed algorithm outperforms the best existing gossip based algorithm in term of execution time.     

Virtual interlining within the European airport network: An airfare analysis

Virtual interlining, which covers the actively marketed or ‘non-hidden’ segment of all potential self-connecting flight itineraries, is often assumed to be a money-saving travel strategy. In this paper we assess the price difference between virtual interlined and ‘traditional’ flight itineraries within the intra-European airport network. We query Kiwi.com's recently developed Tequila platform, one of the few specialised online travel agencies (OTAs) offering both ‘traditional’ and virtual interlined flight itineraries, to obtain information on all available flights in the first week of August, October and December 2019. Using a series of sign tests, we investigate whether a statistically significant fare difference exists between the cheapest available (direct and/or indirect) ‘traditional’ and virtual interlined flight itineraries. Our results indicate a statistically significant fare difference between the cheapest indirect ‘traditional’ and the virtual interlined flight itineraries in favour of the latter. However, with regard to direct traditional flight itineraries the results are mixed. We explore the size and the scope of these patterns in more detail, and outline possible avenues for further research.     

基于ANP-PP-SPA的区域洪灾风险评价模型研究

针对现有洪灾风险评价模型的缺陷与不足,从致灾因子、孕灾因子、承灾因子和减灾因子4个方面,通过对14项评价指标的分析与计算,构建洪灾风险评价体系。洪灾风险评价体系以网络层次分析法(ANP)求解主观权重,投影寻踪法(PP)求解客观权重,主客观综合权重与集对分析理论(SPA)耦合,构建基于ANP-PP-SPA的洪灾风险评价模型。以广东省英德市为例,验证洪灾风险评价模型的适用性。计算结果表明,英德市2016年的洪灾风险属于中等级别,符合英德市2016年的实际情况。洪灾风险评价模型不仅综合考虑了评价指标间的相互关系,还较好地体现了洪灾风险的模糊性和随机性,能够为区域洪灾风险决策和洪水管理提供科学依据。