上海市统计局与新经济企业签署《战略合作协议》

鉴于电子商务部、互联网的迅速发展给零售行业带来深远的变化,影响并逐渐改变消费者的购物体验与购物行为,为了充分利用电子商务企业的大数据与技术优势,提高工作的效率,扩大企业数据的社会影响力,服务社会公众,     

信息化影响评估：业务流程视角的电子商务扩展

 基于创新扩散理论,提出一个信息化影响的测度模型用于评估企业电子商务扩展——从传统渠道转向基于internet电子商务的程度,模型包括相关影响因素和假设命题。按照业务流程观点,用价值链上各职能部门业务流程的电子化实施程度作为电子商务扩展的度量,并收集156家传统实体企业数据验证模型的有效性和假设命题,分析信息化影响的关键因素及其贡献。研究发现企业信息化与电子商务扩展之间存在重要关系,5个因素与行业类别对电子商务扩展影响显著,而企业规模与所有制不是关键因素。本研究提出的测度模型能够有效地测评信息化影响,这对于支持政府和帮助企业制定和建立相关发展战略和方针政策、提供有利条件促进电子商务健康发展,有着重要意义和价值。     

网络会计中电子原始数据的审核与确认

电子商务（ElectronicCommerce＼ElectronicBusiness）是指企业与企业之间、企业与消费者之间，利用现代信息化网络以电子数据信息流通的方式所进行的各类商贸活动。它已成为网络时代的商业方式和企业的生存方式，互联网使得财务会计系统的环境和内容都发生了深刻的变革，这种变革必然要求传统的财务会计进行相应的改革，以适应网络的要求，适应网络要求的会计我们称之为网络会计，网络会计也成为了电子商务的重要组成部分。所谓网络会计指在互联网环境下对各种交易和事项进行确认、计量和披露的会计活动。然而，网络会计意味着大多数的业…     

大数据视域下的企业统计创新——生产型企业统计问题与对策研究

大数据时代，传统生产型企业如何加强企业自身与周边相关数据信息的统计与分析是一个亟待关注的问题。本文对生产型企业发生的数据现状与特点进行了总结与概括，深入分析了企业统计工作中存在的精细化程度不够、数据实时性不够等问题，并结合生产型企业的特点，从五个方面提出改进措施，希望对企业提升统计分析能力，以数据支撑科学决策提供一定的借鉴价值。     

城市群经济网络与经济增长——基于大数据与网络分析方法的研究

借助大数据时代下获得的海量数据,本文分析了长三角城市群的经济网络特征,重点研究了城市群经济网络的增长效应。首先,构建了长三角城市群的人口流动网络、企业组织网络与电子商务网络,对其各自的网络结构特征进行了对比。其次,将网络分析方法与空间计量模型结合起来,使用扩展的J检验方法对不同网络结构下的模型设定方法进行了识别,考察了经济网络带来的溢出效应对于城市群经济增长的影响。分析结果显示,三种经济网络下长三角城市群均呈现出了“中心-外围”的网络结构,其中上海、杭州、苏州、南京及无锡位于城市群经济网络的核心圈层。对网络结构的模型识别结果显示,中心城市在长三角城市群经济网络的溢出效应中扮演着重要角色。具体而言,在人口流动网络下,资本、政府行为存在显著为负的网络溢出效应;在企业组织网络下,人口规模、对外开放呈现出显著为正的网络溢出效应;在电子商务网络下,政府行为存在显著为负的网络溢出效应,对外开放呈现出显著为正的网络溢出效应。     

对人口普查数据质量控制的探讨

人口普查数据是为全国和各地的区域发展、产业布局、生态建设、政府管理与公共服务提供规划和决策的科学依据。因此,人口普查数据质量的高低直接关系到政府各项政策措施的制定和执行效果。本文深入分析了我国人口普查数据质量控制存在的问题,从普查方法、质量评估、人员机构、技术创新等方面提出了加强数据质量控制的措施。     

基于DEA-Benchmarking的企业人力资源绩效评价

企业人力资源是企业管理的重要内容,因此,科学、准确的测量企业人力资源绩效可以为企业决策者提供有效的管理信息.鉴于企业人力资源包括企业员工知识结构、企业员工管理程度和企业组织管理三个部分,文章采用DEA-Benchmarking模型与方法测度企业人力资源效率,从而可以确定出人力资源管理最优的标杆企业,并可为其他企业提供绩效改进的参考信息.     

提高网络会计信息系统安全的措施

一、网络会计信息系统安全 　　目前开展电子商务企业的网络一般体系结构,其中商务运作采用B/S三层体系结构,企业内部业务处理和数据管理采用C/S结构.在技术上,外部网络与企业内部网络采用TCP/IP协议互联,外部用户与企业网络采用WEB技术进行数据交换.……     

电子商务环境下我国第三方物流企业发展研究

1、电子商务与第三方物流的内在联系电子商务将物流业提升到了前所未有的高度,为其提供了空前的发展机遇;电子商务高效的运行效率需要高效的物流运作与之相配套,第三方物流成为满足企业电子商务配送需求的首选;电子商务赋予第三方物流新的特点.电子商务的发展给全球物流业带来新的变化,使现代第三方物流具备了一系列新的特点:信息化,自动化,网络化,个性化.     

数据科学的发展与人才培养研究

梳理了数据科学学科形成与发展的四个阶段——正式诞生、涵义演变、专业发展、广泛应用,概述了国内外对数据科学人才的需求态势和人才培养现状,并提出了具体的人才培养策略:厘清概念认知,明确专业人才的知识结构;编译主干课程的教材,构建数据科学课程群;通过高校、政府和企业的协同育人,培养多类型的专业人才;积极开发软硬件,创建高质量的大数据实践实训平台。     

For Your Information

Abstract

The criteria for selecting a serials management system are often the same as those for selecting an integrated library system in toto. In the post-selection/production environment, the library–vendor relationship matures as a new operational framework is established. Serials management systems must become more efficient and make better use of electronic commerce, especially as a greater emphasis is placed on access to electronic journals (e-journals). Serials Review 2002; 28:93–101.     

基于GMDH的商业银行电子银行业务发展影响因素研究

电子银行业务发展影响因素是国内外学者重点关注的问题之一,采用自组织数据挖掘方法,客观、自动地筛选商业银行电子银行发展的主要影响因素,寻求电子银行业务发展与其影响因素之间的非线性关系。研究结果表明,电子银行交易额增长率、产品规划、网络营销和电子商务发展是电子银行业务的主要影响因素。前一期的电子银行交易额增长率和产品规划对电子银行业务发展的影响较大。网络营销对电子银行业务影响的持续时间较长,其与产品规划的交互作用的影响较大。电子商务通过与前期电子银行业务增长率的交互作用对电子银行发展产生影响。     

电子商务客户网络购物行为挖掘

电子商务已经成为越来越多的消费者购物的一个重要途径，分析网络购物客户的个人特征及其购物行为，对商业的成功有着至关重要的作用。然而电子商务还是一个崭新的商业领域，很多的业界人士仍忙于技术方面的考虑，却很少分析客户的网络购买行为。而使用真实网络购物KDD Cup 2000数据，分析Gazelle．com公司客户的个人特征和网络购物行为，并应用数据挖掘的购物篮模型对各商品之间的关联性进行分析，才能更确切地预测模型预测客户的忠诚度。     

Multivariate online regression analysis with heterogeneous streaming data

New data collection and storage technologies have given rise to a new field of streaming data analytics, called real-time statistical methodology for online data analyses. Most existing online learning methods are based on homogeneity assumptions, which require the samples in a sequence to be independent and identically distributed. However, inter-data batch correlation and dynamically evolving batch-specific effects are among the key defining features of real-world streaming data such as electronic health records and mobile health data. This article is built under a state-space mixed model framework in which the observed data stream is driven by a latent state process that follows a Markov process. In this setting, online maximum likelihood estimation is made challenging by high-dimensional integrals and complex covariance structures. In this article, we develop a real-time Kalman-filter-based regression analysis method that updates both point estimates and their standard errors for fixed population average effects while adjusting for dynamic hidden effects. Both theoretical justification and numerical experiments demonstrate that our proposed online method has statistical properties similar to those of its offline counterpart and enjoys great computational efficiency. We also apply this method to analyze an electronic health record dataset.     

Mixed-Poisson Point Process with Partially-Observed Covariates: Ecological Momentary Assessment of Smoking

Ecological Momentary Assessment is an emerging method of data collection in behavioral research that may be used to capture the times of repeated behavioral events on electronic devices, and information on subjects' psychological states through the electronic administration of questionnaires at times selected from a probability-based design as well as the event times. A method for fitting a mixed Poisson point process model is proposed for the impact of partially-observed, time-varying covariates on the timing of repeated behavioral events. A random frailty is included in the point-process intensity to describe variation among subjects in baseline rates of event occurrence. Covariate coefficients are estimated using estimating equations constructed by replacing the integrated intensity in the Poisson score equations with a design-unbiased estimator. An estimator is also proposed for the variance of the random frailties. Our estimators are robust in the sense that no model assumptions are made regarding the distribution of the time-varying covariates or the distribution of the random effects. However, subject effects are estimated under gamma frailties using an approximate hierarchical likelihood. The proposed approach is illustrated using smoking data.     

Communicating E-resource Management Needs to Library Stakeholders: Theory and Praxis

Abstract

Conflict management studies and the communication needs addressed by the NASIG Core Competencies standards will be the framework for how to communicate electronic resource management to library stakeholders. This article provides both theory and praxis as it is applied at Kansas State (K-State) Libraries for electronic resource access ticket resolution. The librarians responding to these tickets at K-State Libraries assessed their communications and workflows in the past year to provide a more effective customer service model. This provides evidence of technical services having public-facing elements in its core activity.     

数据大集中环境下的统计生产流程再造

随着中国经济结构的不断调整和经济现象的日益复杂化,现有政府统计面临极大的挑战。基于此,以制度领域、技术领域和管理领域的数据大集中为核心架构,构建一种新型的政府统计数据大集中环境,并依托该环境对中国政府统计生产流程进行再造。     

Using Markov Chains for Non-perennial Daily Streamflow Data Generation

The use of Markov chains to simulate non-perennial streamflow data is considered. A non-perennial stream may be thought as having three states, namely zero flow, increasing flow and decreasing flow, for which a three-state Markov chain can be constructed. Alternatively, two two-state Markov chains can be used, the first of which represents the existence and non-existence of flow, whereas the second deals with the increment and decrement in the flow for periods with flow. Probabilistic relationships between the two alternatives are derived. Their performances in simulating the state of the stream are compared on the basis of data from two different geographical regions in Turkey. It is concluded that both alternatives are capable of simulating the state of the stream.     

Imputation procedures for categorical data: their effects on the goodness-of-fit chi-square statistic

An imputation procedure is a procedure by which each missing value in a data set is replaced (imputed) by an observed value using a predetermined resampling procedure. The distribution of a statistic computed from a data set consisting of observed and imputed values, called a completed data set, is affecwd by the imputation procedure used. In a Monte Carlo experiment, three imputation procedures are compared with respect to the empirical behavior of the goodness-of- fit chi-square statistic computed from a completed data set. The results show that each imputation procedure affects the distribution of the goodness-of-fit chi-square statistic in 3. different manner. However, when the empirical behavior of the goodness-of-fit chi-square statistic is compared u, its appropriate asymptotic distribution, there are no substantial differences between these imputation procedures.