基于PLSSEM的在线消费中交易成本的影响因素研究

交易成本是影响消费者购买意愿的重要因素,分析交易成本的影响因素对于促进消费具有积极意义。在对在线交易中交易成本相关文献研究的基础上,设计了在线消费中交易成本影响因素的假设命题,通过PLS--SEM模型,利用调研数据,对消费者在线消费中交易成本的影响因素进行定量分析。研究表明,购买频率和不确定性因素显著地影响交易成本,不确定性影响作用较大,并最终对购买意愿产生影响。     

Nonparametric Kernel Methods with Errors‐in‐Variables: Constructing Estimators,Computing them,and Avoiding Common Mistakes

Estimating a curve nonparametrically from data measured with error is a difficult problem that has been studied by many authors. Constructing a consistent estimator in this context can sometimes be quite challenging, and in this paper we review some of the tools that have been developed in the literature for kernel‐based approaches, founded on the Fourier transform and a more general unbiased score technique. We use those tools to rederive some of the existing nonparametric density and regression estimators for data contaminated by classical or Berkson errors, and discuss how to compute these estimators in practice. We also review some mistakes made by those working in the area, and highlight a number of problems with an existing R package decon .     

我国经济有效增长研究--基于自然资本库兹涅茨曲线的经济学分析

有效经济增长不同于传统集约增长,是经济增长与自然资本相协调的增长范畴.本文在对自然资本库兹涅茨曲线内涵进行新的概括基础上,展开经济学分析,指出它对谋求经济增长的发展中国家的启示和局限性,并给出我国实现经济有效增长和新型工业化道路的政策选择.     

Conditional expectation determination based on the J-process using Malliavin calculus applied to pricing American options

The aim of our paper is to elaborate a theoretical methodology based on the Malliavin calculus to calculate the following conditional expectation (P_t(X_t)|(X_s)) for s≤t where the only state variable follows a J-process [Jerbi Y. A new closed-form solution as an extension of the Black—Scholes formula allowing smile curve plotting. Quant Finance. 2013; Online First Article. doi:10.1080/14697688.2012.762458]. The theoretical results are applied to the American option pricing, consisting of an extension of the work of Bally et al. [Pricing and hedging American options by Monte Carlo methods using a Malliavin calculus approach. Monte Carlo Methods Appl. 2005;11-2:97–133], as well as the J-process (with additional parameters λ and θ) is an extension of the Wiener process. The introduction of the aforesaid parameters induces skewness and kurtosis effects, i.e. smile curve allowing to fit with the reality of financial market. In his work Jerbi [Jerbi Y. A new closed-form solution as an extension of the Black–-Scholes formula allowing smile curve plotting. Quant Finance. 2013; Online First Article. doi:10.1080/14697688.2012.762458] showed that the use of the J-process is equivalent to the use of a stochastic volatility model based on the Wiener process as in Heston's. The present work consists on extending this result to the American options. We studied the influence of the parameters λ and θ on the American option price and we find empirical results fitting with the options theory.     

Reducing Customer Dissatisfaction: How Important is Learning to Reduce Service Failure?

As service failures are inevitable, firms must be prepared to recover and learn from service failures. Yet, the majority of customers are still dissatisfied with the way firms resolve their complaints. Can learning to reduce service failures reduce customer dissatisfaction, and to what extent are such reductions sustainable? Previous research showed that organizational learning curves for customer dissatisfaction (i) follow a U‐shaped function of operating experience and (ii) are heterogeneous across firms. In this paper, I tease out where the U‐shaped learning‐curve effect and learning‐curve heterogeneity originate: service failure or customers' propensity to complain with a third party given the occurrence of a service failure. Using quarterly data for nine major US airlines over 11 years, I find that the U‐shaped learning‐curve effect and the learning‐curve heterogeneity originate in the propensity to complain. In the long term, reductions in service failure did not translate in sustainable reductions in customer dissatisfaction. Customers' propensity to complain eventually went up. Managing the propensity to complain provides more opportunity for a firm to distinguish itself from competitors.     

区域经济增长与环境污染关系的实证分析——以安徽省为例

通过对安徽省1995—2009年期间经济增长指标和三类环境污染指标的选取,以计量分析方法考察安徽省经济增长和各类环境污染指标之间的作用机制,结果显示安徽省三类环境污染指标的环境库兹涅茨曲线没有呈现倒U型,而是随着经济增长波动较大,呈现N型等关系曲线。针对分析结果,从优化地区产业结构、增大地方财政支持力度、加强区域环境污染监控与治理三个方面提出对安徽省经济可持续发展的对策建议。     

基于FPGA的高频等精度频率计设计与实现

文章介绍了等精度频率计误差分析和实现原理,在Altera新一代FPGA/PLD开发软件QuartusⅡ 中运用硬件描述语言Verilog HDL编程,通过单片机控制EP1 C12Q240I7芯片实现等精度频率计的设计,频率计可通过分频测量800 MHZ～1 400 MHZ之间的高频信号频率,大大提高了测量精度,实验证明测量精度为0.000 03％以下.     

基金资助论文与无基金资助论文被引情况分析:以部分高水平医学期刊为例

选择基金资助论文作为高水平论文,对其被引用情况进行分析,同时与无基金资助论文的被引情况进行比较,以探讨二者被引情况存在的差异.结果表明,被引用过的基金资助论文的单篇被引频次并不比无基金资助论文高,而基金资助论文的被引率显著高于无基金资助论文.由此可见,论文的引用率可推广应用于表示期刊的水平.     

基于交易频率的农产品交易机制选择研究

我国农产品交易频率主要受农产品生产的自然资源依赖性、生产和消费的即时性、时空分布的非均衡性以及农产品的小规模经营特征的影响。因此,在农产品交易活动市场依赖度日趋提高的背景下,根据农产品交易频率特征,建立以农产品中介经纪组织和经纪人为主要载体的交易机制,是降低农产品交易频率的有效措施。     

基于不平顺谱的轨道不平顺状态评价与识别探讨

线路不同区段轨道质量参差不齐,但其幅频差异能很好地在各区段轨道不平顺功率谱密度（PSD）曲线上得到表征。基于此,结合沪宁客运专线轨检数据,从识别和评价两个方面对轨道平顺状态进行了研究。基于不同区段轨道谱存在幅频特性差异,提出以200 m为一研究单元,通过分频段离散各单元轨道谱幅频信息,以三维图的形式进行不平顺的时频域识别分析。借鉴轨道谱分级管理的方法,同时综合波段整体不平顺和波段内各波长幅值波动程度两项指标,研究并给出了评价各里程单元平顺性的方法,将综合评价后各区段所属不平顺状态等级划分为优秀、良好、合格、失格。