基于网络外部性的价值模块整合与兼容性选择

本文分析了价值模块的网络外部性特征，并基于网络外部性研究了价值模块整合过程中的兼容性选择和价格竞争行为。研究结果表明：当由进入厂商选择兼容度时，兼容性越高进入厂商的市场份额越大，并能够获得更高的市场价格；当由在位厂商选择兼容度时，兼容度增加将减少消费者的转移成本，使更多的模块需求商转向购买进入厂商的产品，减少了在位厂商的市场份额；当转移成本的兼容性敏感系数较低时，在位模块供应商能够获得更高的价格，而当转移成本对兼容性很敏感时，较高的兼容度将迫使在位模块供应商降低价格。价值模块的网络外部性加剧了模块供应商之间的竞争，进一步促进了价值模块整合和产业融合的过程。     

基于神经网络系统的项目投资风险评价探讨

与传统的评价方法不同，神经网络模型具有自学习、自组织、自适应能力等的特点，它较好的克服了传统项目评价局限性以及依赖专家经验的弊端，为项目投资风险评价开辟了新途径。论文阐述了神经网络结构与原理，分析了项目投资风险评价的神经网络模型，通过应用评价，进一步探讨其应用价值及其意义。     

基于企业基因重组理论的价值网络构建研究

全球化、信息化带来市场交易成本的急剧下降，并直接导致组织创造价值的方式发生了变化。本文借鉴企业基因和企业基因组的概念，对企业基因重组理论进行了系统地完善和整合。依此理论为基础，本文对能力要素驱动型价值网络的形成、特征和构建策略进行了深入地分析。     

Developing a Community of Practice: Michael Gaffikin and Critical Accounting Research

This paper demonstrates the role of a community of practice in academic endeavour, focusing on the influence of place and the role of thought leaders in guiding academic development. This is illustrated with reference to the influence of Emeritus Professor Michael Gaffikin in establishing a critical accounting community of practice at the University of Wollongong (UOW) through his PhD supervisions. Social network analysis (SNA) is used to visualize the 43 PhD supervisions undertaken by Gaffikin during his career, and subsequent PhD supervisions of his students, and students of those students. SNA illustrates the structure of relationships, and the paths through which scholars learnt from one another, which we combine with qualitative analysis of recollections, acknowledgments, and doctoral theses. We demonstrate the role of Gaffikin, as the intellectual thought leader, and UOW, as the intellectual place, in the development of the critical accounting community of practice. The development of critical accounting scholarship was a function of Gaffikin's intellectual and professional leadership, which he executed through PhD supervision, the annual Doctoral Consortium, and his direction at UOW. This paper highlights the importance of local communities for the development of research agendas, and the influence of PhD supervisors on the professional development of students.     

Managing and financing metropolitan public services in China: experience of the Pearl River Delta region

Under China’s current fiscal policies and inter-governmental relations, it is a significant challenge to finance and deliver public services across jurisdictions. This challenge was met in the Pearl River Delta region in southern China with a collaborative governance approach. Directives from higher-level governments and horizontal inter-city fiscal arrangements were successfully combined to deliver public services. Effective networks should be developed to improve co-ordination and collaboration in delivering cross-jurisdictional public services.     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.     

On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks

Daily and weekly seasonalities are always taken into account in day-ahead electricity price forecasting, but the long-term seasonal component has long been believed to add unnecessary complexity, and hence, most studies have ignored it. The recent introduction of the Seasonal Component AutoRegressive (SCAR) modeling framework has changed this viewpoint. However, this framework is based on linear models estimated using ordinary least squares. This paper shows that considering non-linear autoregressive (NARX) neural network-type models with the same inputs as the corresponding SCAR-type models can lead to yet better performances. While individual Seasonal Component Artificial Neural Network (SCANN) models are generally worse than the corresponding SCAR-type structures, we provide empirical evidence that committee machines of SCANN networks can outperform the latter significantly.     

基于B/S模式的高校量化管理系统的应用研究

本文分析了目前高校教学量化管理工作中普遍存在的问题和矛盾,提出了一种基于B/S模式的高校教师教学工作量化管理网络化系统的解决方案,论述了系统开发的必要性和实际意义;文章介绍了系统的结构及主要功能模块,以及系统在实践中的应用效果。     

计算机视觉的理论框架探索

本文就计算机视觉的理论框架进行阐述,对计算机视觉理论框架存在的问题进行分析,提出计算机视觉理论框架的新发展,以确保通过计算机视觉获得的景物信息更加完整。     

计算机Linux网络操作系统特点及服务器配置

Linux系统作为一款网络操作系统,它具有很好的网络操作功能,网络操作系统(NOS)是网络的心脏和灵魂,是向网络计算机提供服务的特殊的操作系统。