Spatial movement patterns among intra-destinations using social network analysis

To explore popularly visited tourist locations, travel movement patterns, and movement points, this study collected samples of 321 Chinese tourists and 337 Japanese tourists who were visiting major tourist destinations in Seoul and its vicinity in South Korea. Results of analyzing movement patterns showed that Japanese tourists tend to be clustered around popular attractions, whereas Chinese tourists tend to spread over a larger area of attractions. Some specific shopping and amusement attractions were the locations most popularly visited by both groups. The start points and end points in the two groups’ itineraries were dissimilar overall, even though their patterns were similar in regard to major preferred tourist attractions. Thus, the findings of this study have the potential to contribute to understanding spatial mobility in a tourism destination through tracking tourists’ movement patterns.     

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).     

采用航迹特征的智能机型识别

针对空战目标识别中机型自动识别比较困难的问题，提出了采用航迹特征的智能目标识别方法。利用卷积神经网络（Convolutional Neural Network，CNN）分层学习特征的能力，训练CNN算法模型自动地从航迹数据中学习有用的特征并分类。利用沿海实地采集的15个类别的飞机航迹数据，经一系列数据预处理后作为智能识别算法的训练和测试数据，在验证实验中描述了算法网络的相关配置,对比了CNN与其他分类器的识别结果。实验结果表明，CNN具有很好的识别性能。     

黑龙江旅游网络关注度时空演变特征研究

探究黑龙江旅游网络关注度时空演变特征对黑龙江旅游业良性发展具有重要意义.利用百度指数获取2011—2018年全国和分地区黑龙江旅游网络关注度逐日搜索指数数据.从时间分布、空间分布、时空集聚3个方面研究其演变特征.研究表明:2011—2018年全国黑龙江旅游网络关注度年际变化总体呈现上升趋势,月际变化呈"W"形;2011—2018年31个省区市黑龙江旅游网络关注度空间差异较大、季节性影响显著;东部地区黑龙江旅游网络关注度偏高,西部地区黑龙江旅游网络关注度的季节差异最明显;东部地区内的黑龙江旅游网络关注度差异性最小,西部地区内差异性最大;黑龙江旅游网络关注度具有正空间自相关,部分东部、中部地区表现为高高集聚,多数西部地区表现为低低集聚.     

Platform coopetition in the tourism industry: conflicts and tensions caused by the closure of Booking.com in Turkey

In March 2017, as a result of a precautionary interim decision made by the courts based on the case relating to ‘unfair competition practices’, Booking.com closed its platform for inbound tourism in Turkey and ceased operations. This was the first instance of an online booking platform halting access for inbound bookings for the domestic market. This platform-based relationship involves both cooperation and competition, and thus this paper identifies this relationship as platform coopetition. Based on the governance network theory and employing a case-study approach, the Booking.com case is examined from the viewpoint of tourism coopetition from two perspectives: industry-wide and agent-specific. The paper provides an analysis of these perspectives and the past and on-going process of Booking.com’s platform closure. The constitutive dynamics this case endangers the coopetitive environment of the tourism industry and thus creates destructive uncertainties, especially for small hotels. This analysis also reveals the issues in terms of political representation for digital service platform companies.     

基于转移概率和网络联系的辽宁省农村居民点适宜性评价

[目的]农村居民点适宜性评价在农村居民点调控、规划和预测中具有基础作用,且农村居民点适宜性评价应顾及农村居民点之间的社会经济活动联系。[方法]以辽宁省为研究区,首先运用逐步Logistic回归模型构建农村居民点转移概率,其次运用网络分析方法确定农村居民点图斑间的网络联系强度,最终通过加权求和方法确定农村居民点转化概率,进行农村居民点空间布局适宜性评价。[结果]辽宁省农村居民点可以划分为高度适宜类、较适宜类、一般适宜类和不适宜类4类,分别占农村居民点总面积的比例为28.18%、31.32%、13.26%和27.24%;从各地貌分区来看,高度适宜类主要集中分布在中部平原地区和东部山地丘陵区中的南方沿海地区,而不适宜类整体分布则较为零散;辽宁省中部平原区位条件好,东部沿海地区区位条件也较好,西部山地丘陵区地区较差。[结论]研究方法和结论有助于全面把握农村居民点社会经济与区位适宜性特征,为农村居民点科学规划提供科学指导。     

天地一体化信息网络中天基卫星网络架构设计

为了充分利用各种空间设施资源，提升天基信息网络覆盖与传输能力，分别从天基信息网络体系架构和逻辑功能架构角度进行了系统性设计。与以往天基网络的设计不同，该设计更注重各类卫星网络的深度融合应用，为此将网络虚拟化技术引入天基卫星网络。同时，还提出了解决新架构下卫星组网难题的方法，将电磁涡旋、卫星灵活载荷和边缘计算技术设计到天基网络。仿真表明，所提出的架构能有效提升频谱利用率和减少卫星网络信令开销。     

Unleashing the Power of Networks: Shareholder Activism,Sustainable Development and Corporate Environmental Policy

In recent years, a new trend has emerged in which shareholder activists have formed networks to empower shareholders and magnify shareholder voices. This study explores the structural patterns and effectiveness of shareholder activism networks and shows how those networks affect corporate sustainability policies. We draw upon stakeholder influence theory, stakeholder network management theory and recent studies on activism networks to examine a shareholder activism network formed around environmental issues. The study found that (1) the structure of shareholder activist networks is largely driven by organizational attributes such as organization type, organizations’ human resources, media visibility and history; and (2) activist organizations with high centralities and eigenvector centralities enjoy more efficient results. This study contributes to our understanding of the business responses to shareholder demands on improving environmental performance and paves the way for future research on sustainable development through partnerships with shareholder networks. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

基于冠层光谱和BP神经网络的水稻叶片氮素浓度估算模型

[目的]快速、准确地诊断水稻叶片氮素营养状况,为水稻氮肥精准管理提供依据。[方法]以江西省农科院8种不同施肥处理的晚稻为研究对象,于主要生育期同步测定了水稻冠层光谱反射率及叶片全氮浓度(Leaf Nitrogen Concentration,LNC),系统分析了原始光谱反射率、一阶微分光谱、"三边"参数以及由350～1 350nm两两波段组合的差值(SD (Rλ1,Rλ2))、比值(SR (Rλ1,Rλ2))及归一化(ND(Rλ1,Rλ2))光谱指数与水稻LNC的相关关系,筛选出敏感参数,并以之为自变量构建了水稻LNC的传统预测模型,另外构建不同指标个数的多元线性与BP神经网络模型,并对模型进行验证。[结果](1)水稻LNC与一阶微分光谱在751nm处的相关性最高(r=0. 822);(2)"三边"参数中的红边面积SDr与LNC的相关性较高(r=0. 687);(3) 750nm附近的红边波段与近红外波段差值组合、550nm附近的绿光波段与近红外波段的比值及归一化差值组合与水稻LNC的相关性较高,以SD (R752,R751)、SR (R534,R1 350)和ND (R534,R1 349)表现最好,相关系数分别为0. 827、-0. 790和0. 788;(4)传统回归模型中以SD(R752,R751)构建的一元线性模型最佳(RC2=0. 665、RV2=0. 750、RMSEV=0. 4%、RPD=2. 034);(5)利用5个指标((R'751、SDr、SD (R752,R751)、SR (R534,R1 350)、ND (R534,R1 349))经逐步回归筛选出的2个指标SD ((R752,R751)和SR (R534,R1 350))构建预测水稻氮素的BP神经网络模型,预测效果最佳,其验证参数值分别为R2=0. 859、RMSEV=0. 302%和RPD=2. 669。[结论]基于单指标构建的传统线性模型计算过程简单但精度略低,而基于2个指标(SD (R752,R751)、SR (R534,R1 350))构建的BP神经网络模型预测精度高于该2指标构建的多元线性模型,表明在指标适合的情况下,BP神经网络对氮素具有较好的预测能力,是一种快速准确估算水稻叶片全氮浓度的方法。     

Network analysis of the Caucasus’ image

Destination image is influenced by many factors, including destination promotion materials, the mass media as a general familiarity agent, the perceivers’ own characteristics and even researchers’ methodological choices. To isolate and minimize the impact of research on destination image, different qualitative and quantitative designs and analysis techniques have been utilized. However, no previous study utilized the network analysis technique, which may be useful to reveal a picture of destination image with the interconnections and hidden dynamisms of dimensions as well as its correlates. The present study applies this technique on qualitative data from an online sample of Americans on their perceptions of a relatively remote and unfamiliar destination, the Caucasus region, in order to hone in on the dramatic impact of mass media on destination image. Results revealed networks of meanings with residue of mass media messages about Boston bombing, with some differences among different genders and education levels.