The role of network embeddedness across multiple social networks: Evidence from mobile social network games

This article examines peer influences from network relationships within a social network game (i.e., embeddedness) and across such games (i.e., multiplexity). Drawing on social influence theory, we develop a bivariate Poisson model of users’ repeated visits and latent attrition that accommodates peer interaction after controlling for homophily. We estimate the model using data from two social network games with considerable overlap among network members. We find that friends who are only multiplex across games exert greater peer influence on users’ game visits than members who are embedded within a single game. We also determined that ignoring network multiplexity across games may lead firms to mistarget users due to biased peer influences of embedded friends. This result provides an unresearched explanation—strength of peer influence—for the mixed findings in previous literature on network embeddedness. We utilized our results to conduct several scenario analyses to demonstrate how firms can effectively manage users’ engagement and target users in multiple social network games.     

Complex Network of Aviation E-Services in the Belt and Road Initiative: A Heuristic Study of Small Data based on Block Modeling

ABSTRACT

The aviation e-service system is an important part of support for business communication in regions covered by Belt and Road initiative. In exploring the role of airline companies in this system, we examine the structure of the network, which consists of airlines interconnections based on small data of individual attributes of aviation companies in aviation e-services, and study these interconnections across different groups using block modeling. The heuristic solution of airline companies in development of international communication and cooperation is further discussed. Among our policy implications for global managers, we suggest the enhancement of cross-regional cooperation among airlines.     

The ‘Blogosphere’ as a platform for interpretative phenomenological analysis: the case of TEFL tourism

The use of the Internet is becoming increasingly integral to the day-to-day operations of society, facilitating an interconnected and globalised world, where geographic barriers are no longer a defining criteria for communication. This opens the researcher up to a realm of research opportunities, which to-date have been under-exploited. This paper contributes to the wider body of literature addressing the concept of Online research, demonstrating in practice how it can be utilised in the context of interpretative phenomenological analysis. It is argued that netnography is akin to interpretative phenomenological analysis (IPA) in that it accounts for an individual’s personal perception or account of an event or state, as opposed to attempting to produce an objective record. This paper outlines how blog analysis can be utilised in the context of IPA, demonstrating how this worked in practice during the initial exploratory research phase of the teaching English as a foreign language tourism phenomenon.     

Trade networks and economic fluctuations in Asian countries

The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess its strength in forecasting economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with the US, EU and UK, we detect the community structure of the evolving network and we identify clusters and central nodes inside each of them. Our findings show that data are well represented by two communities, in which People's Republic of China and Japan play the major role. We then analyze the synchronisation between GDP growth and trade. Furthermore we apply our model to the prediction of economic fluctuations. Our findings show that the model leads to an increase in predictive accuracy, as higher order interactions between countries are taken into account.     

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.     

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。     

现代网络安全技术分析

随着网络技术的广泛应用，网络安全也越来越受到重视。本简述了网络安全问题的定义和TCP／IP协议的安全漏洞。同时，介绍了当前网络采用的安全技术。     

一类有向网络的容量扩张问题研究

将网络容量定义为最大流的流量。针对网络容量的三种扩张方式：点扩张、弧扩张、点扩张和弧扩张相结合,分别建立数学模型,提供算法;在分开讨论的基础上,还提出了统一的容量扩张模型;最后提供了一个具体算例。     

基于Elman神经网络的商业银行信贷风险识别及评估模型

建立了基于Elman神经网络的商业银行信贷风险识别及评估模型，并通过实例验证了模型的准确性和可靠性。研究过程及结果表明，基于Elman神经网络的商业银行信贷风险识别及评估模型能够很好地反映信贷过程中的非线性因素，准确地预测出完整的信贷风险评估指标和信用等级之间的映射关系，能快速评估和有效减低商业的信贷风险。一组实例结果显示该评估模型的准确率接近90％。     

网络多媒体在旅行社业务中的应用初探

从旅行社的旅游业务出发，分析目前旅行社所面临的国际、国内形势，根据旅行社实际业务运作情况探讨网络多媒体在其中的实际应用，针对旅游电子商务的发展趋势提出了目前施行社应充分应用网络多媒体的必要性和重要性。