Platform selection by software developers: Theory and evidence

This paper analyzes platform selection (affiliation) by game developers in the Japanese home video game industry. We develop an elementary model of affiliation by software developers and propose the hypothesis that wider availability of game titles for a platform positively inclines game developers to affiliate with that platform when releasing new game titles. Then, using data for Japan, we estimate a multinomial logit model that includes both the attributes of game developers and the characteristics of platforms, and find evidence supporting this hypothesis. Overall, the findings suggest that game developers expect the indirect network effect to apply, and the prospect of future growth matters to them when deciding with which platform to affiliate.     

网络流行语中民众网络话语权研究

网络流行语作为网络文化的产物，映射当下现代文明的各类现状。通过挖掘网络流行语内在起因、情境和心理，以反沉默螺旋法则为理论依据，研究当代民众网络话语权的产生、表达方式和表达心态以及相关应对机制。希望通过本研究对我国社会行政管理科学化进程有所助益。     

Information transmission between large shareholders and stock volatility

Does information transmission between large shareholders exacerbate stock volatility or reduce stock volatility? In this study, based on the common shareholding data in the Chinese stock market from 2007 to 2017, we establish the shareholder’s coshareholding network, and use the weighted network clustering coefficient to measure the information transmission speed. Moreover, we investigate the impact of information transmission speed on stock volatility. The empirical results show that a nonlinear U-shaped relationship exists between information transmission speed and stock volatility. The findings are robust to the inclusion of other determinants of stock volatility identified in the literature. Finally, we verify the existence of private information interaction in the coshareholding network.     

Systemic financial risk early warning of financial market in China using Attention-LSTM model

We propose an Attention-LSTM neural network model to study the systemic risk early warning of China. Based on text mining, the network public opinion index is constructed and used as a training set to be incorporated into the early warning model to test the early warning effect. The results show that: (i) the network public opinion is the non-linear Granger causality of systemic risk. (ii) The Attention-LSTM neural network has strong generalization ability. Early warning effects have been significantly improved. (iii) Compared with the BP neural network model, the SVR model and the ARIMA model, the LSTM neural network early warning model has a higher accuracy rate, and its average prediction accuracy for systemic risk indicators has been improved over short, medium and long terms. When the attention mechanism is included in the LSTM, the Attention-LSTM neural network model is even more accurate in all the cases.     

How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis

In this empirical study, a five-stage methodology is used to examine the efficiency of 45 worldwide known airline companies from the financial, operation and marketing perspectives. Initially, the superefficient data envelopment model is run with inputs and outputs that are selected based on the literature review. However, because 21 out of 45 airline companies are found to be efficient based on this analysis, a stepwise regression-based mechanism is applied to four reduced models – one for each output variable – for better discrimination. The outputs are, namely, net profit margin (financial output), passengers carried, on-time departure performance (operational outputs), and customer satisfaction (marketing output). In this way, the significant input variables are found for each reduced model. In the third stage, in order to provide even more discrimination, social network-based eigenvector centrality values are used as the weights of the superefficiency scores, and the strengths and weaknesses of efficient airlines for each output are specified in terms of their related significant inputs. The results show that, when net profit margin is taken as an output, Vietnam Airlines has the top weighted superefficiency value and excels in terms of available seat kilometers and liquidity, but it should improve its debt level. Although Norwegian Airlines has the highest efficiency with respect to debt level, it is not the best role model because its eigenvector centrality value is relatively low. However, Norwegian airlines also has the highest weighted superefficiency and acts as a role model in terms of on-time departures with respect to this output. Its main strength is liquidity, and it has no significant weaknesses. On the other hand, in terms of overall satisfaction and passengers carried, Vietnam Airlines and Thai Airways are the leaders, respectively. Vietnam Airlines is the only superefficient company with respect to overall satisfaction, while the basic strengths of Thai Airways in terms of passengers carried are its employee and fleet, and it has no significant weakness. A final aggregation of the results is made by making pairwise comparisons of the relative importance of four outputs for 7 experts selected from different departments of airline companies. According to the results, Net Profit Margin has the highest priority, followed by On-time Departure and Overall Customer Satisfaction, while passengers carried has the lowest importance. Based on these relative priorities, it can be said that Vietnam Airlines can be accepted as the top performing airline company, followed by Norwegian Airlines.     

Evolution of FDI flows in the global network: 2003–2012

As one type of international capital flow, FDI maintains its important role in globalization. This article attempts to investigate the evolution of the FDI flows from a network perspective. Based on the bilateral FDI flows data between countries from 2003 to 2012, we construct the global FDI flows network for each year and thus quantify network measures (such as flow volumes and connections); further by analysing the tendency and changes of these network measures during the past 10 years, we delineate the features and dynamics of the FDI flows in the global network. We have the following findings: (a) the flows network changes during and after the crisis, i.e. flow volume fallen down and recovered, and flow connection restructured with more diversity; (b) the global FDI flows network is getting more loosely connected; (c) individual countries vary in different patterns.     

Prioritizing destination attributes for optimal resource allocation: a study of Chinese tourists visiting Britain

ABSTRACT

This study assesses the importance, performance, and the interrelationships of key destination attributes for marketing managers to prioritize resource allocation. A three-dimensional analysis of importance–performance–impact-analysis (IPIA) factors, based upon a survey sample of 275 Chinese tourists to Britain and an expert panel interview with 10 destination marketing managers is presented. Data analysis was based upon a mix of multi-criteria decision-making methodologies, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and the Analytic Network Process (ANP) method. The framework can be applied to prioritize resources allocation to improve customer satisfaction in other contexts, such as a sector or a specific business.     

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。     

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。     

iSDS: a self-configurable software-defined storage system for enterprise

ABSTRACT

Storage is one of the most important aspects of IT infrastructure for various enterprises. But, enterprises are interested in more than just data storage; they are interested in such things as more reliable data protection, higher performance and reduced resource consumption. Traditional enterprise-grade storage satisfies these requirements at high cost. It is because traditional enterprise-grade storage is usually designed and constructed by customised field-programmable gate array to achieve high-end functionality. However, in this ever-changing environment, enterprises request storage with more flexible deployment and at lower cost. Moreover, the rise of new application fields, such as social media, big data, video streaming service etc., makes operational tasks for administrators more complex. In this article, a new storage system called intelligent software-defined storage (iSDS), based on software-defined storage, is described. More specifically, this approach advocates using software to replace features provided by traditional customised chips. To alleviate the management burden, it also advocates applying machine learning to automatically configure storage to meet dynamic requirements of workloads running on storage. This article focuses on the analysis feature of iSDS cluster by detailing its architecture and design.