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.     

External pressure or internal culture? An innovation diffusion theory account of small retail businesses’ social media use

COVID-19 put unprecedented external pressure on small businesses to adopt or increase use of social media while not all small businesses are internally ready for this rapid change. This study investigated the roles of external pressures and organizational culture of openness and learning in driving small retail business owners'/managers' social media use decisions by impacting their perceived usefulness and barriers, based on the innovation-decision process model from the diffusion of innovations theory and the theory of reasoned action. An online survey with structured measurements was administered to 411 U.S. small retail business owners/managers. Results from structural equation modeling revealed that external pressures positively influenced small business owners'/managers’ perceived usefulness and barriers and social media use intention. In addition, the culture of openness and learning positively influenced the perceived usefulness while mitigating the perceived barriers, thereby directly and indirectly influencing the social media use intention. Theoretical and managerial implications are discussed.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

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.     

Uncertainty,story-telling and transformative learning: An instructor’s experience of TEFI’s Walking Workshop in Nepal

ABSTRACT

This article recounts three stories from TEFI’s walking workshop in Nepal: the construction of a road through what was once a trekking path; a dance-floor encounter at a Himalayan party; and the arrival of one participant, fatigued by jet lag and disoriented by the new surroundings. These stories of confusion, discomfort and fear are linked by one common theme: the potential of uncertainty to foster deep reflection and nuanced conclusions. The premise that uncertainty is to be valued and even cultivated has been explored in educational theory, spiritual traditions, and research on transformative learning. These sources affirm the role of uncertainty in the process of knowledge creation. However, accepting this role can be challenging for educators because it requires they assume a new identity, one which they may perceive as being at odds with their status as “teacher” the identity of learner. One way for the educator to address this challenge may be through recounting their own stories of uncertainty. Stories of being immersed in unfamiliar situations that challenge, confuse and even frighten – stories, in other words of being a tourist – can foster reflection on an intellectual, emotional and spiritual level, engaging the “whole” person, and thus initiating the educator/learner’s transformative journey.     

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.     

Firm-specific assets and the internationalization–performance relationship in the U.S. movie studio industry

We study the role that firm-specific assets (FSAs) play in the processes underlying the internationalization–performance relationship. International business scholars have begun studying the interrelationship between FSAs, internationalization, and performance; however, this research is still emergent, and has produced inconclusive results. We believe that this may be due, in part, to research designs involving the same FSAs across many industries, even though individual industries may rely on different FSAs in their internationalization strategies. We address this issue in a single industry study of U.S. movie studios, which typically rely on blockbuster production capabilities as FSAs in their internationalization efforts. We show how these FSAs co-evolve with firms’ degree of internationalization, and how each factor mediates the positive effect of the other on performance. Our results highlight the importance of studying specific industries and their salient FSAs when assessing their role of such resources in the internationalization–performance relationship.     

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。