The new wave of AI-powered luxury brands online shopping experience: The role of digital multisensory cues and customers’ engagement

Academic literature retains a dearth of empirical evidence of the cutting-edge aspect of artificial intelligence (AI)-powered digital assistance and digital multisensory cues, despite the prospect of these factors on real-life customers' luxury brand online shopping experience. Thus, the aim of this study is to examine the significant pathway and effects of AI-powered digital assistance toward customers’ luxury brand online shopping experience. Drawing on S–O-R (Stimulus, organism, and response) and TRAM (Technology Readiness and Acceptance Model) paradigm, a multi-method research design was deployed to investigate constructs. Firstly, semi-structured interviews were utilized to explore customers' online behavior under the luxury brands and information technology aspect. Secondly, survey data were collected and analyzed by using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The PLS-based analysis of quantitative data confirmed the exploratory insights of qualitative findings, establishing the connections of AI-powered digital assistance, customer engagement, and customers' luxury brand online shopping experience. Research findings also suggest that customer engagement plays a mediation role in the relationship between AI-powered digital assistance and customers' luxury brand online shopping experience. Besides, digital multisensory cues moderate the relationship between AI-powered digital assistance and customer engagement. Further, fsQCA complements the findings of PLS-SEM that reveal the significant combination of factors that lead to the perceptions of customers' luxury brand online shopping experience.     

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.     

The importance of consumer multihoming (joint purchases) for market performance: Mergers and entry in media markets

Consumer “multihoming” (watching two TV channels, or buying two news magazines) has surprisingly important effects on market equilibrium and performance in (two‐sided) media markets. We show this by introducing consumer multihoming and advertising finance into the classic circle model of product differentiation. When consumers multihome (attend more than one platform), media platforms can charge only incremental value prices to advertisers. Entry or merger leaves consumer prices unchanged under consumer multihoming, but leaves advertiser prices unchanged under single‐homing: Multihoming flips the side of the market on which platforms compete. In contrast to standard circle results, equilibrium product variety can be insufficient under multihoming.     

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.     

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。     

欧盟视阈下在线平台中个人数据的增值税处理

近年来,在线平台的迅猛发展推动了全球经济数字化加速转型,但同时也引发了包括增值税政策适用在内的诸多挑战.通过研究《欧盟增值税指令》和欧州法院的判例法,以及分析个人数据与在线平台运行之间的关系可以推断出,个人数据是在线平台提供访问服务构成的增值税应税范围内的供应,且与消费者是否向在线平台支付金钱形式的对价无关.在实践中,使用客观价值方法来确定在线服务供应的应税金额存在实际困难,而使用直接联系标准解决易货交易问题,会导致增值税税基在本质上得到扩张.因此,建议当前不要将在线平台访问服务的供应视为一项应税交易.此外,对于商家为获得消费者数据而向平台付款的情形,因其不符合直接联系标准,也不应被视为服务对价.     

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.     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.