江苏网络经济发展现状及对策研究

网络经济在国民经济中正扮演着越来越重要的角色,是我国经济发展新的增长点。江苏省是我国网络经济和电子商务应用较为发达的地区之一,研究江苏网络经济的发展对于江苏乃至全国的网络经济发展都具有重要意义。通过调查江苏省网络经济的发展现状,分析存在的问题,提出了相关改进措施和优化建议,以推动江苏省网络经济更加健康、良好的发展。     

Network,knowledge and relationship impacts on innovation in tourism destinations

We combine network structure and firm-level relationship measures to explore the association between innovative behavior, firm position within the network of a destination, and the knowledge and relational trust characteristics of a firm's innovation-oriented relationships. We find current collaboration, shared knowledge and trust are associated with innovative behavior with partner firms, but that betweenness centrality indicates which partners are the most prominent innovators in a population. That is, relationship-level characteristics facilitate innovation partnerships, but network structure characteristics identify the most successful innovative partners. To theory, our findings contribute to efforts in the tourism, innovation and network literature to evaluate the differential effects of knowledge stocks and flows on innovation. For practice, our results suggest that promoters of innovation within a destination should leverage brokerage positions to improve the in-flow of ideas while encouraging the firms that share knowledge and trust to collaborate to apply those ideas.     

Microfoundations of network exploration and exploitation capabilities in international opportunity recognition

While international entrepreneurship (IE) recognizes opportunity recognition (OR) as a central activity and the prominent role of network capabilities in OR, it is not informative as to how different network capabilities influence OR in international markets. We utilize dual network capability through the lens of exploration-exploitation to better understand how these two different capabilities influence the identification of international opportunities. Given that microfoundations perspective and prior experience in IE are under-developed and under-theorized, we explore founder’s prior experience as an essential microfoundation for the dual network capability. By employing structural equation modeling on a sample of 647 early internationalizing firms from a developing country, the study demonstrates that founders’ prior experience is a significant microfoundation of dual network capability in international OR. However, both exploration and exploitation capabilities fail to bring new opportunities in a changing market environment. A post-hoc analysis reveals that at a higher level of market change, younger firms benefit more from network exploration, whereas older firms achieve greater success when leveraging benefits from network exploitation. The study concludes with implications and future research avenues.     

Geography of Italian student mobility: A network analysis approach

Understanding the phenomenon of intra- and international student mobility has become increasingly relevant to the organization of tertiary education systems. Using microdata information provided by the Italian National Student Archive on the cohorts of students enrolled at university in the academic years 2011–12 and 2014–15, we consider a network analysis approach to investigate the incoming and outgoing student flows between territories and universities. More specifically, the paper aims to shed light on the dynamics of Italian student mobility networks at both the bachelor's and master's degree levels by considering attractiveness indicators combined with network centrality measures, clustering techniques for network data and explanatory models. We analyze the partition of the global network structure by means of blockmodeling analysis and we explain the determinants of the differences among universities in attracting students adopting a quantile regression analysis.     

Intangible resources of competitive advantage: Analysis of 49 Asian airlines across three business models

Without sustainable competitive advantage firms have limited economic reasons to exist and will decline. Competitive advantage concerns the factors which provide competitive strength. This paper is based upon the resource-based view which considers firm resources to be heterogeneous and which believes that firms only have a small bundle of core resources irrespective of their overall performance. This research establishes the role of 36 intangible resources for 49 Asian airlines across three business models: network airlines; low-cost subsidiaries from network airlines; and low-cost carriers. It uses the VRIN framework which examines whether resources are valuable, rare, inimitable, and non-substitutable. Research participants distribute points between their chosen seven resources according to their perceived role in firm performance. Resources which meet all four requirements of VRIN are considered core competences and sources of sustained advantage. Across all 49 Asian airlines, the top-three most important resources of advantage are slots, brand, and product/service reputation. While these core resources are predictable, they have not previously been proven within the context of airlines, let alone geographically and by airline model. Results show that the core bundle of resources vary for each model, which helps to explain the difference in performance across models, and that some resources which were expected to be high-ranking, such as organisational culture and customer focus, were not.     

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.     

非洲铁路发展需求分析与市场开发策略

中资企业面向非洲铁路市场,多以"广覆盖"的形式投入开发,一定程度上造成了资源浪费。为优化中资企业在非洲铁路市场布局以及资源配置,在分析非洲铁路发展现状、铁路网发展影响因素基础上,基于铁路系统需求度、铁路发展需求度分析非洲铁路发展需求,提出了非洲大陆49个国家高、较高、中、低4个等级的铁路发展需求度,同时提出非洲铁路市场开发策略建议,即:优化非洲铁路市场开发资源配置,分区域实施铁路市场开发及项目建设,创新合作模式、拓宽资金来源。     

军民融合社会关系网络对军民融合新创企业成长的影响

军民融合新创企业是推动我国国防建设和社会经济融合发展的重要力量，军民融合社会关系网络具有丰富的异质性资源，可以有效促进军民融合新创企业成长。借鉴社会网络理论，构建以关系深度、关系广度、关系高度为代表的军民融合社会关系网络、耦合共生与军民融合新创企业成长理论模型，通过对收集的304份军民融合新创企业问卷数据进行实证分析，结果发现：军民融合社会关系网络对军民融合新创企业成长具有正向影响；耦合共生在军民融合社会关系网络与军民融合新创企业成长间发挥中介作用；创业导向显著调节耦合共生与军民融合新创企业成长的关系。     

Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach

We construct the complete network of tail risk spillovers among major cryptocurrencies using the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression. We capture important features of the network, including major risk-driving and major risk-receiving currencies, and the evolution of the tail dependence among the currencies over time. Importantly, we reveal a striking finding that the right tail dependence among the cryptocurrencies is significantly stronger than the left tail counterpart. This unique characteristic may have contributed to the rise in popularity of cryptocurrencies over the last few years. Our portfolio analysis reveals that diversification in cryptocurrency investment can be accomplished simply by employing the naïve equal-weighted scheme even when transaction costs are taken into account.     

Study of emerging air taxi network operation using discrete-event systems simulation approach

This research focuses on understanding the air taxi operations to determine the number of air taxis required to fulfill the demand for urban air mobility in New York City (NYC). We leverage the Define, Measure, Analyze, Design, and Verify (DMADV) framework and integrate it with the systems simulation approach. Upon investigation, we find that all the parameters linearly impact the vehicle utilization, while other measures are robust, specifically with respect to the seating capacity. It is also recommended to operate initially with 70 air taxis in NYC to achieve a trade-off between customer wait time and vehicle utilization. The proposed approach can act as a recommender system for air taxi companies.