信息技术对审计的影响研究

随着信息技术在社会经济生活中的全方位渗透,适用于传统经济环境的审计理论、方法与技术需要变革以适应现代组织的各类日常运营和活动,通过调研信息技术在审计中的具体应用,从12个方面对信息技术进步与审计发展面临的问题和趋势进行系统性研究。研究认为,信息技术促使审计职能从审计为主变为审计与管控并重,审计范围从经济安全变为经济与信息安全并重,审计内容从财务为主变为财务与业务并重,审计对象从账本变为数据库,审计模式从事后变为事前事中事后全包含,审计方式从现场勘察为主变为远程分析为主,审计介质从纸质变为电子,审计证据从有形变为无形,数据来源从抽样变为全样本,测试内容从人工系统变为信息系统,工作形式从审计合作变为审计协同,风险计算从依赖审计人员经验变为依据系统模型,这些变革极大地推进了审计向现代化方向发展。     

北京主导优势产业链发展战略

本文分析了北京工业发展的优势和劣势以及当前面临的主要问题,在此基础上提出了未来北京工业发展的新思路。作者认为,北京工业发展应面向京津冀和环渤海地区,实行大工业、大市场的一体化战略,即适当控制和强化那些具有突出优势的核心部分,而甩掉或转移扩散那些不具有优势或优势不突出的非核心部分,打造一体化的开放式跨区域主导优势产业链。当前,应着重打造八条一体化的开放式产业链。     

艺术画作授权产业价值链分析

创意产业的蓬勃发展,创意经济的持续增长,创意潜能的有效激发离不开创意产业链的形成和完善。本文选择创意产业中的典型——艺术画作授权产业为研究对象,探讨了艺术画作授权产业的经济和社会价值,以及该产业链的构成。分析艺术画作授权产业链的价值增值和传递,是对创意产业链研究的有益尝试。     

回收竞争下考虑CSR行为的闭环供应链定价决策及协调

研究考虑企业社会责任(CSR)行为的闭环供应链定价决策及协调问题,分别构建了单个第三方回收及两个第三方回收竞争下的闭环供应链博弈模型,分别从企业与消费者两个视角分析了CSR投入对供应链成员的定价策略及系统总收益的影响,并建立了基于“收益共享”与“回收成本共担”相结合的契约协调模型。研究表明,两个第三方回收商间的适度竞争不仅可以降低产品价格、提升废旧产品回收效率,同时对提高企业的CSR投入水平以及收益水平也起到积极的促进作用。最后,在契约参数的可行性范围内,“收益共享-成本共担”契约在使供应链总收益达到最大的同时,还成功改善了每个成员企业的收益。     

消费者展厅行为和参考质量效应对O2O供应链动态运营策略的影响

本文研究消费者展厅行为和参考质量效应对O2O供应链动态运营策略的影响问题。分析了集中决策、分散决策和制造商分担实体店服务成本决策3种模式下的制造商产品质量策略、实体店和电商平台的服务竞争策略,以及品牌商誉变化和企业利润等问题。并进行了价格、实体店访问比例和展厅行为强度对企业绩效的影响。研究发现：展厅行为会挫伤实体店提供服务的积极性,降低品牌商誉,从而损害制造商和实体店的利润水平;而消费者的这种搭便车行为会提高电商平台利润,但由于参考质量效应的存在,其提升空间有限。综合而言,展厅行为对供应链总体绩效不利。应对展厅行为的长期战略有：1)加强上下游的纵向合作,制造商分担实体店服务成本契约,能实现供应链总体绩效的帕累托改进。2)从受展厅行为影响最大的实体店角度,保持线下产品高定价、高服务水平,提升消费者支付意愿,全面提升实体店的品牌溢价能力,获取长久生存之道。     

Binary probability maps using a hidden conditional autoregressive Gaussian process with an application to Finnish common toad data

The Finnish common toad data of Heikkinen and Hogmander are reanalysed using an alternative fully Bayesian model that does not require a pseudolikelihood approximation and an alternative prior distribution for the true presence or absence status of toads in each 10 km×10 km square. Markov chain Monte Carlo methods are used to obtain posterior probability estimates of the square-specific presences of the common toad and these are presented as a map. The results are different from those of Heikkinen and Hogmander and we offer an explanation in terms of the prior used for square-specific presence of the toads. We suggest that our approach is more faithful to the data and avoids unnecessary confounding of effects. We demonstrate how to extend our model efficiently with square-specific covariates and illustrate this by introducing deterministic spatial changes.     

Analysis of Competing Risks by Using Bayesian Smoothing

We consider the competing risks set-up. In many practical situations, the conditional probability of the cause of failure given the failure time is of direct interest. We propose to model the competing risks by the overall hazard rate and the conditional probabilities rather than the cause-specific hazards. We adopt a Bayesian smoothing approach for both quantities of interest. Illustrations are given at the end.     

Bayesian inference for stable Lévy–driven stochastic differential equations with high‐frequency data

In this paper, we consider parametric Bayesian inference for stochastic differential equations driven by a pure‐jump stable Lévy process, which is observed at high frequency. In most cases of practical interest, the likelihood function is not available; hence, we use a quasi‐likelihood and place an associated prior on the unknown parameters. It is shown under regularity conditions that there is a Bernstein–von Mises theorem associated to the posterior. We then develop a Markov chain Monte Carlo algorithm for Bayesian inference, and assisted with theoretical results, we show how to scale Metropolis–Hastings proposals when the frequency of the data grows, in order to prevent the acceptance ratio from going to zero in the large data limit. Our algorithm is presented on numerical examples that help verify our theoretical findings.     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

信息不对称下价格随机的应急数量折扣契约研究

以市场需求和市场价格随机波动的二级供应链为研究对象,寻找其在信息不对称条件下绩效优化的路径。通过显示原理分别构建生产成本和销售成本信息不对称时应急供应链的数量折扣契约模型,得到最优订货量与最佳批发价策略。通过具体的算例加以验证,分析了信息不对称程度对供应链上成员及整个供应链绩效的影响。研究结果表明：当突发事件造成市场价格随机波动和市场需求变化时,供应链上的跟随者能从隐瞒私人信息中获利。但当市场需求增大时,整个供应链绩效受损,反之则反是。这与以往研究在市场需求随机、市场价格固定和信息不对称条件下的结论迥异。