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.     

A new perspective on the exporter productivity premium: online trade

We use a unique firm-level data set including 9000 companies from 26 European Union countries covering four different sectors to take a close look at the relationship between online exports and productivity. The online exporter productivity premium is estimated using different techniques (ordinary least squares, quantile regressions and robust estimation). Results consistently indicate that the estimated online exporter productivity premium is statistically different from zero, positive and significant from an economic point of view. European online exporters, according to these results, are approximately 2% more productive than non-online exporters. Productivity differences between firms could be related to variables that are not included in the empirical model. More research would be needed to address this issue in the future.     

跨境电商对华商网络贸易的效应分析

在就跨境电商对华商网络贸易所具有的替代效应与互补效应进行理论分析的基础上，利用古诺模型分析市场均衡的结果及贸易效应，采用面板数据实证检验跨境电商对华商网络贸易的影响，结果表明跨境电商对华商网络贸易的互补效应大于替代效应：一方面，由于华商网络对出口贸易的影响尤为显著，而跨境电商平台又以出口贸易为主，从而跨境电商对华商网络出口贸易的影响较大；另一方面，跨境电商平台偏向于差异化产品贸易，因而跨境电商对差异化产品的华商网络贸易有着较大影响。也就是说，跨境电商对华商网络贸易的互补效应在出口贸易与差异化产品贸易上表现得尤为显著。     

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.     

COVID-19 and retail: The catalyst for e-commerce in Belgium?

Since the turn of the century especially small, local retailers struggle with the advent of e-commerce. It is hence no surprise that the retail sector is one of the hardest-hit sectors in the current pandemic. To understand the short- and longer-term impacts of COVID-19 on retail, we conducted two surveys to understand ongoing changes in the sector. By contrasting changing consumer behavior with the actions taken by local retailers, we assess whether the current pandemic is potentially a catalyst for e-commerce in Belgium. We do this based on a newly constructed framework of e-retail accessibility, as the differences between online and physical retail require a revision of the traditional economic geographical perspective on retail performance as introduced by Christaller (1933). We conclude that the COVID-19 pandemic holds ample opportunities for an increase in the three components of e-retail accessibility, but that a lack of professionalism might prevent traditional local retailers to retain a share of the expanded online market. This could well mean the final blow for local brick and mortar shops if, as is predicted, the share of online shopping in total retail expenditure remains high after the pandemic.     

邻近性与创新合作：最新研究进展

自邻近性理论提出以来，邻近性在创新合作网络及其演化中的作用得到了很多学者的关注，相关研究丰富而庞杂。从邻近性因素对创新合作的影响、邻近性因素在创新合作中的相互作用以及创新合作对邻近性因素的影响等方面梳理了当前的研究进展，力图在邻近性因素与创新合作构成的复杂系统中厘清相互关系与动态作用机制。在此基础上，针对当前研究中尚未明晰和解决的问题，进一步提出了未来研究中有待持续深入的议题。     

Resource Dependence and Network Relations: A Test of Venture Capital Investment Termination in China

This study examines how venture capital (VC) firms terminate investments in an emerging economy context. We contend that due to the weak institutional environment, it is appropriate to draw on insights from power and social relation perspectives for a better understanding of the phenomenon. Specifically, we argue that a termination decision hinges on not only the dependence relationship between a VC firm and its portfolio companies, but also the social relationships among VC firms. Event history analyses of approximately 12,000 VC deals made in China between 2001 and 2012 reveal that when a VC firm has a greater number of investments in an industry, it is more likely to terminate investments on a portfolio company in that industry. Moreover, such effect on termination is moderated by the focal VC's embeddedness with its syndicate partners and collaboration opportunities with other VC firms outside the immediate access of the syndicate partners. Our study sheds light on research on VC decision making in emerging markets by integrating insights from resource dependence relationships and interorganizational network characteristics.     

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.