VC治理行为中介作用下的关系专用性投资与技术创新绩效

以风险投资“关系型融资”机制为视角,立足资源基础理论与交易成本理论,在“关系租”起源与“关系型融资”价值创造机制探讨的基础上,构建关系专用性投资、VC治理行为与技术创新绩效关系整合模型,研究不同关系专用性投资属性对技术创新绩效的影响以及VC治理行为的中介作用.通过264家科技型创业企业调研所得数据进行实证分析,研究显示,实物型关系专用性投资与VC监控行为正相关,与VC增值服务负相关,VC监控行为与技术创新绩效负相关;知识型关系专用性投资与VC监控行为负相关,与VC增值服务正相关,VC增值服务与技术创新绩效正相关.VC治理行为在关系专用性投资与技术创新绩效的关系中具有部分中介效应.     

基于VC++6.0添加用户的设计与实现

为了保证全国等级考试能够正常并且顺利的进行,要对服务器和考试机用户进行添加设置。利用VC++6.0实现对服务器添加KSGROUP组,考试机添加Administrators组的成员,考试机才可以以这个用户登录进行考试,使得每台考试用的考试机操作的目录相互独立,不能互相访问,保证系统的安全性。     

我国创业投资的制度选择

创业投资是一种向发展潜力巨大的新建企业提供股权资本的投资行为.本文从制度经济学的角度,分析了创业投资有效运行的原理和制度要求,在此基础上分析了我国发展创业投资事业的利弊因素以及目前我国发展创业投资亟需推进的制度创新,希望能对我国创业投资事业的健康发展具有一定的借鉴意义.     

The empirical analysis of the -bilateral optimized combinatorial auction model

This study proposes a new and highly efficient dynamic combinatorial auction mechanism—the N-bilateral optimized combinatorial auction (N-BOCA). N-BOCA is a flexible iterative combinatorial auction model that offers more optimized trading for multiple suppliers and purchasers in the supply chain than one-sided combinatorial auction. We design the N-BOCA model from the perspectives of market architecture, trading rules, and decision strategy for winner determination, the decision strategy for winner determination needs flexible optimization modeling capability. Thus rule-based reasoning was applied for reflecting the flexible decision strategies. We also show the viability of N-BOCA through Paired Samples T-test experimentation. It shows that N-BOCA yields higher purchase efficiency and effectiveness than the one-auctioneer to multi-bidders (1-to-N) combinatorial auction mechanism.     

An investigation of the attention effects of venture capitalist backing on entrepreneurial firms

In this paper, we predict that venture capital (VC) backed initial public offerings (IPOs) will attract more attention than non-VC-backed IPOs, as VCs offer important signals to investors searching for information about entrepreneurial firms. We use a measure developed by Google (i.e., Trends) to capture the spikes in investors' attention experienced by firms in the time period surrounding their IPOs. Our results demonstrate that firms backed by VCs enjoy a far greater spike in attention than their counterparts. Furthermore, we find that firms with more prominent VCs, a larger number of VCs, and VCs situated at farther geographic distances exhibit significantly greater spikes in investors’ attention during the week of their IPO. Combined, the findings show a clear demarcation between entrepreneurial firms with or without VC backing, they bring to the fore new upshots stemming from the relationship between VCs and entrepreneurial firms, and they raise new potential questions on this relationship and beyond.     

Estimation and selection procedures in regression: An L1 approach

The authors consider the problem of estimating a regression function go involving several variables by the closest functional element of a prescribed class _G that is closest to it in the L₁ norm. They propose a new estimator ? based on independent observations and give explicit finite sample bounds for the L₁distance between ?g and go. They apply their estimation procedure to the problem of selecting the smoothing parameter in nonparametric regression.     

ISD4000系列语音芯片开发平台设计

针对ISD4000系列语音芯片的应用,设计出语音芯片开发平台。给出了单片机的硬件设计方法和软件设计流程图,分析了上位机软件的开发工具和软件设计方法。该开发平台可以把上位机中的语音信息录制到ISD4000系列的语音芯片中,也可以把母片上的语言拷贝到子片中。测试结果表明,该平台可以可靠地把声音信息录制到语音芯片中。     

基于ADO技术的LED数据库显示

针对LED显示屏系统对数据库的需要,采用基于W++6.0语言开发工具的ADO技术开发面向不同类型的数据库,使LED显示屏系统与数据库开发技术结合在一起,实现LED显示屏上的各种不同类型数据库的滚屏显示。     

Asymptotics and bootstrap for random-effects panel data transformation models

This article investigates the asymptotic properties of quasi-maximum likelihood (QML) estimators for random-effects panel data transformation models where both the response and (some of) the covariates are subject to transformations for inducing normality, flexible functional form, homoskedasticity, and simple model structure. We develop a QML-type procedure for model estimation and inference. We prove the consistency and asymptotic normality of the QML estimators, and propose a simple bootstrap procedure that leads to a robust estimate of the variance-covariance (VC) matrix. Monte Carlo results reveal that the QML estimators perform well in finite samples, and that the gains by using the robust VC matrix estimate for inference can be enormous.