大数据技术在企业内部审计中的应用

在大数据技术的支持下,可充分挖掘数据信息价值,为企事业单位的经营和管理创造有利的技术条件。现代企业内部审计中需要面对大量的审计数据,工作量偏大,如能借助大数据技术完成审计信息收集和处理,则可显著提升内部审计成效。鉴于此,本文对大数据技术在企业内部审计中的应用现状进行分析,并探究有效的应用策略,以期充分发挥大数据技术的应用优势,助力内部审计工作的高效、高质量开展。     

基于OLAP的零售业销售分析系统设计与实现

开发了三层C/S模式的基于OLAP的零售业销售分析系统,系统能够对多维数据集中的数据进行更新,能够实现对多维数据集的切片、切块、钻取及聚合分析,为决策者制定科学合理的销售决策计划提供了有力依据。     

随机存放点和体积下拣货路径问题研究

针对货物存放点和货物体积的不确定性,提出应用交叉熵法解决拣货车路径问题的方法,由于目标函数的复杂性,设计一种基于Monte—Carlo抽样求解路径期望距离的有效方法。为了提高标准交叉熵（cE）法的性能,设计了随分位值大小发生变化的更新Markov转移矩阵关键路径的自适应调整算法。计算结果验证了采用该方法解决此问题的鲁棒性和有效性。     

土性参数的相关距离研究

在自然过程中形成的土,其物理力学性质指标具有自相关的特性,这种特性可用相关距离来衡量。对于岩土工程参数的统计计算应考虑相关距离的影响,这样能更真实、准确的反映地基土的特性。以西安市地铁一、二号线勘察的静力触探数据,根据Vanmarcke提出的土层概率模型、土性相关距离的定义以及方差折减函数Γ(2h)的基本性质,采用递推空间法计算得出各地基土层的相关距离。     

随机存放点和体积下拣货路径问题研究

针对货物存放点和货物体积的不确定性,提出应用交叉熵法解决拣货车路径问题的方法,由于目标函数的复杂性,设计一种基于Monte-Carlo抽样求解路径期望距离的有效方法.为了提高标准交叉熵(CE)法的性能,设计了随分位值大小发生变化的更新Markov转移矩阵关键路径的自适应调整算法.计算结果验证了采用该方法解决此间题的鲁棒性和有效性.     

面向存储对象的动态负载平衡研究

负载均衡是大规模基于对象存储系统必须要考虑的重要问题。为此以系统总响应时间为代价函数,以对象被访问频率为依据,建立一种将对象复制与对象迁移统一在内的动态负载均衡模型,并充分利用存储设备的智能实现系统的动态负载均衡。仿真结果表明,在存在大量热点访问和对象分布不均匀的情况下,启用对象复制和对象迁移的负载均衡算法能最大程度的减少系统的平均总响应时间。     

基于区间分析的公交客流推导方法

通过大数据可以更加精确地推导公交站点上下车客流区间。利用公交GPS(Global Positioning System,全球定位系统)定位数据、IC卡(Integrated Circuit Card,集成电路卡)刷卡数据,生成区间数形式的公交客流需求更具实践意义。文章首先基于30m半径的站点缓冲区生成车辆到站时刻表,并利用时间匹配法推导上车站点,其次考虑乘客出行距离、站点周边土地利用情况、客流吸引强度、站点换乘系数建立公交下车站点概率推导模型,然后运用区间分析理论,采用置信区间优化算法计算区间数形式的公交客流需求。最后以苏州市1021路公交为期4周的刷卡数据为例进行实例分析。     

大数据情境下企业价值创造路径及效果评价

在现代市场竞争中,大数据应用为企业价值创造和竞争优势提升提供了新路径。通过相关理论回顾,本文阐述了大数据的资源属性,从价值链和知识管理双重视角分析了企业基于大数据进行价值创造的路径,提出了基于大数据的价值创造和价值增值评估模型,得出如下结论:大数据是具有VRIN属性的战略性资源;基于大数据的价值创造是企业动态整合虚实价值链以构建价值创造系统的过程,是对外部知识搜寻以实现企业知识耦合和创新的螺旋式升级过程。因此,建议企业重视大数据资源,尝试构建基于大数据的价值创造系统,利用大数据加强知识管理,从而提升企业竞争优势。     

大数据环境下企业内部控制探究

随着科学技术及互联网的快速发展,当今社会已经跨入大数据时代,其对经济发展产生了重要影响,同时也对企业传统的内部控制环境、风险评估、控制活动、信息交流、内控监管等都造成很大的冲击。企业经营环境、人员构成、业务活动、经营管理等都较以往更加复杂,风险因素也日趋增多。在这种形势下,企业极有必要加强内部控制,并有效运用大数据技术,以提高企业生产经营效率和抗风险能力。本文基于大数据时代背景,首先介绍企业内部控制的概念与价值;然后再分析目前企业内部控制的现状,汇总整理出财务数据真实性易受影响、内部控制风险系数增大、稽核监督实施难度大、内控体系更新不够及时、信息沟通渠道不够顺畅等五个方面的问题;最后提出强化企业内控的相应策略,通过建立信息化内控环境、健全信息化安全管理机制、加强动态风险监控、更新内部控制系统以及构建交流平台提高信息传输速度等具体措施,确保企业内部控制管理取得理想的成效,进而促进企业更好发展。     

通用报表系统实现技术探微

一、问题的提出 通用报表系统主要用来灵活实现企业报表的呈现与打印。目前，我国的通用报表系统主要用于财务与会计报表的呈现与打印，都表现为类似EXCEL的风格特点，可用操作EXCEL表格的方法（或类似方法）操作这些系统。这类系统都存在着不能真正实现灵活的数据源取数的问题。目前的通用报表系统是不可以自定义取数源与取数函数或公式的，而只能选择系统提供的有限的取数函数或公式来自定义报表，如果需要实现对这些取数函数或公式以外的数据资源的访问，如取非财务数据制作管理报表或者需要更灵活地进行取数就不方便了。一个真正灵活的报表系统应该可以自定义取数源、取数函数或公式以及变量，且能与EXCEL兼容。     

构建先进的广西区委党校校园网络数据中心

校园网络数据中心是校园信息系统应用建设快速发展的关键。随着校园网络的不断扩大及各类业务应用系统的加入,原有的直联数据存储系统应用方式由于数据分散存储、缺少数据保护机制的架构而面临严峻考验。随着业界虚拟化的资源整合技术和CDP连续数据保护技术的出现,改造传统存储系统、构建先进的校园网络数据中心将成为我们的必然选择。     

Turning from crime: A dynamic perspective

This paper examines criminal choice using a variant of the human capital model. The innovation of our approach is that it attempts to disaggregate individual capital, not unlike production-based studies which disaggregate physical capital into equipment and structures. We disaggregate an individual’s capital stock into the standard human capital component as well as a utility generating component that we call social capital. In our set-up, social capital is used to account for the influence of social norms on the decision to participate in crime. This is done by modeling the stigma of arrest as a reduction in the individual’s social capital stock. We also allow individuals to account for the impact of their criminal actions on their probability of arrest. In order to estimate the structural parameters underlying the model, we make use of computationally intensive methods involving simulated generalized method of moments and value function approximation. The empirical results, based on panel data from the Delinquency in a Birth Cohort II Study, support the social capital model of crime and reveal significant state dependence in the decision to participate in crime.     

商业地产项目全寿命周期成本的价值分析决策模型

应用全寿命周期成本的价值分析技术,将寿命周期中各项成本不确定性也作为衡量方案优劣程度的因素。根据各项成本概率分布,利用蒙特卡罗仿真技术计算各方案全寿命成本的分布函数,利用价值分析结果选择最优方案。克服了传统分析方法考虑因素单一、实际值和期望值存在较大偏差的缺点。在商业地产项目方案投资决策中具有一定的应用价值。     

Distance and academic performance in higher education

This paper examines whether one of the determinants of academic performance in higher education is the geographical distance separating the place of study and the place of family residence. Twelve years of data on students from a public university are utilized to estimate a model of relative academic performance, with an instrumental variables two-stage least squares estimator to account for possible endogeneity bias. The results indicate that distance is a negative determinant of academic performance and provide a new factor to take into account in reflexions over the impact of the spatial organization of higher education institutions.     

价值工程思想在企业技术创新战略选择中的应用

企业在选择技术创新战略时应综合考虑企业自身情况。从价值工程的角度分析了企业技术创新战略的功能与寿命周期成本;在此基础上得出不同战略类型的价值,并以此为企业技术创新战略选择提供决策参考。     

An analysis of the bounds for the Gini coefficient

The bounds on the Gini coefficient obtained by Gastwirth for the case of grouped data are considered. While the population bounds will always include the value of the population Gini coefficient and the estimated bounds will always include a suitably chosen estimate of the Gini coefficient, estimated bounds need not include the value of the population Gini coefficient.The distributions of the estimators of the bounds are considered and it is shown that a failure to take account of sampling variation can lead to very misleading results. In fact, increasing the number of income groups used tends to decrease the difference between the bounds, but the relative frequency with which the estimated bounds includes the population Gini coefficient decreases. The relationship between sample size, the nature of income groups and estimator precision is considered.     

Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor

Abstract

This paper considers the problem of prediction in a panel data regression model with spatial autocorrelation in the context of a simple demand equation for liquor. This is based on a panel of 43 states over the period 1965–1994. The spatial autocorrelation due to neighbouring states and the individual heterogeneity across states is taken explicitly into account. We compare the performance of several predictors of the states’ demand for liquor for 1 year and 5 years ahead. The estimators whose predictions are compared include OLS, fixed effects ignoring spatial correlation, fixed effects with spatial correlation, random-effects GLS estimator ignoring spatial correlation and random-effects estimator accounting for the spatial correlation. Based on RMSE forecast performance, estimators that take into account spatial correlation and heterogeneity across the states perform the best for forecasts 1 year ahead. However, for forecasts 2–5 years ahead, estimators that take into account the heterogeneity across the states yield the best forecasts.     

On evaluating the equivalency of alternative MDS representations

A typical question in MDS is whether two alternative configurations that are both acceptable in terms of data fit may be considered “practically the same”. To answer such questions on the equivalency of MDS solutions. Lingoes & Borg (1983) have recently proposed a quasistatistical decision strategy that allows one to take various features of the situation into account. This paper adds another important piece of information to this approach: for the Lingoes-Borg decision criterion R, we compute what proportion of R-values is greater/less than the observed coefficient if one were to consider all possible alternative distance sets within certain bounds defined by the observed fit coefficients for two alternative MDS solutions, what are the limits of acceptability for such fit coefficients, and how are the observed MDS configurations interrelated.     

Analysing corporate forest disclosure: How does business value biodiversity?

Corporations are failing to account for their impact on biodiversity despite accelerating extinctions. The value of biodiversity to business can be explained by an environmental philosophy spectrum, where perspectives range from anthropocentric (humans are prioritised) to ecocentric (all life is equal), made up of paradigms and values linked to biodiversity protection. We explore the biodiversity values conveyed by the 40 largest corporations responding to the CDP Forest Questionnaire using 28 specific yes/no criteria aligned with the environmental philosophy spectrum. Strong anthropocentric perspectives focused on economic contribution dominated, conveying a desire to protect company reputation, thereby legitimising operations. Corporations seemingly only protect biodiversity that hold material benefits for humans. Some biocentric/ecocentric perspectives were conveyed in terms of extinction risk and sometimes intrinsic value. This could be a response to the accelerating global biodiversity crisis, offering hope corporations can protect all forms of biodiversity and could evidence ecocentric leadership informing business strategy.     

Multivariate Clustered Data Analysis in Developmental Toxicity Studies

In this paper we review statistical methods for analyzing developmental toxicity data. Such data raise a number of challenges. Models that try to accommodate the complex data generating mechanism of a developmental toxicity study, should take into account the litter effect and the number of viable fetuses, malformation indicators, weight and clustering, as a function of exposure. Further, the size of the litter may be related to outcomes among live fetuses. Scientific interest may be in inference about the dose effect, on implications of model misspecification, on assessment of model fit, and on the calculation of derived quantities such as safe limits, etc. We describe the relative merits of conditional, marginal and random-effects models for multivariate clustered binary data and present joint models for both continuous and discrete data.