科技型小微企业创新生态系统网络治理研究

建立一个完整、高效的创新生态系统是破解科技型小微企业创新困境、提高创新效率，以及助力新旧动能转换的有效途径。基于生态系统理论和演化动力学模型，构建科技型小微企业创新生态系统网络框架和网络联结模式，利用竞争、互利共生和捕食关系演化模型，分析演化模型的均衡点及其稳定条件。结果发现，创新生态位重叠程度决定了竞争激烈程度，系统演化均衡条件是主体间分工程度高，且嵌入适度。最后，从价值主体和机构主体两个方面〖JP〗提出推进科技型小微企业创新生态系统不断进化的治理策略。     

嵌入性创新网络与科技型小微企业创新绩效:网络能力中介效应研究

科技型小微企业嵌入于创新网络中,通过自主性发挥网络构建与管理能力,进一步分享创新网络资源,提高创新实力。基于中国软件谷(南京)及相关创业孵化园246家软件企业问卷调查结果,运用SPSS、LISREL软件进行统计分析,实证研究网络能力对嵌入性创新网络与科技型小微企业创新绩效的中介效应。结果表明:(1)嵌入性创新网络稳定性有利于科技型小微企业创新绩效的提升;(2)嵌入性创新网络强度越大,科技型小微企业网络能力越强;(3)科技型小微企业网络能力越强,创新绩效提升越明显;(4)科技型小微企网络能力有助于促进嵌入性创新网络对创新绩效的提升作用。     

国家重点科技资源支撑区域创新经济产出的空间差异研究

根据2011-2014年科技部《国家重点科技基础条件资源调查表》以及国家统计年鉴数据,首先,使用赫芬达尔指数定量描述了利用国家重点科技资源进行创新活动的非均衡性。其次,使用网络DEA方法,实证分析了2012-2014年中国(内地)各省份国家重点科技资源对区域创新发展的支撑作用。研究表明,国家重点科技资源对区域创新发展的支撑作用不仅取决于资源创新生产阶段,而且受制于重点科技资源支持下的区域创新发展阶段。重点科技资源的支撑作用还有较大提升空间,70%的省份创新成果转化能力有待提高,且大部分省份的国家重点科技资源未实现优化配置。此外,全国及东部、中部和西部国家重点科技资源对区域创新发展的支撑效率不存在绝对收敛趋势。     

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.     

How to inhibit a partner's strong and weak forms of opportunism: Impacts of network embeddedness and bilateral TSIs

This study investigates the moderating effects of a firm's network embeddedness and a partner's transactional specific investments (TSIs) on relationships between the firm's TSIs and its partner's strong- and weak-form opportunism, and compares the efficiency among these moderator variables. The regression results suggest that (1) a firm's TSIs are positively related to partner's opportunism when network embeddedness and the partner's TSIs are relatively low; but (2) a firm's TSIs are negatively related to partner's opportunism when network embeddedness and the partner's TSIs are relatively high. Furthermore (3) network embeddedness is more effective in inhibiting partner's weak-form opportunism than in inhibiting strong-form opportunism resulting from the firm's TSIs. Finally (4) with regard to the relationship between TSIs and weak-form opportunism, the negative moderating effect of network embeddedness is greater than the negative moderating effect of partner's TSIs. This study explains reasons why conflicting views exist about the relationship between TSIs and partner's opportunism, reveals the differences in the moderating effects of network embeddedness and partner's TSIs, and makes new contributions to both transaction cost theory and embeddedness literature. It also provides, for firms involved in TSIs in a buyer–supplier relationship, insightful managerial suggestions about ways to reduce their partner's varying forms of opportunism.     

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.