Towards a meta-theory of accounting information systems

The purpose of this paper is to articulate a model for accounting information systems (AIS) research that synthesizes the primary theoretical perspectives of the extant literature. Building on the three orientations used in prior research (technological, organizational and cognitive approaches) and adopting an explicit systems perspective, we develop a model that links system design alternatives to the three orientations and to task performance. The model places a central focus on the accounting task and suggests a matching process between requirements of the task and system design alternatives at multiple levels of analysis. We also demonstrate how the application of the model suggests future research opportunities, organized around four research propositions.     

Model uncertainty and systematic risk in US banking

This paper uses Bayesian Model Averaging to examine the driving factors of equity returns of US Bank Holding Companies. BMA has as an advantage over OLS that it accounts for the considerable uncertainty about the correct set (model) of bank risk factors. We find that out of a broad set of 12 risk factors only the market, real estate, and high-minus-low Fama–French factors are reliably related to US bank stock returns over the period 1986–2010. Other factors are either only relevant over specific subperiods or for subsets of bank holding companies. We discuss the implications of our findings for empirical banking research.     

投资者情绪是导致我国投资者对市场信息出现反应偏差的原因吗：基于贝叶斯分位数回归模型的研究

本文使用贝叶斯分位数回归模型实证分析包含投资者情绪的投资者最优选择模型,结果表明：投资者情绪对于股票收益率存在非线性的正向影响,这是造成投资者对于市场信息出现反应偏差的一个重要原因.同时,市场信息和投资者情绪指标对于我国股票收益率都有着较大的影响作用;当股票出现不同涨跌幅时,市场信息对于股票收益率的影响有着较大的差异性.而考虑了投资者情绪指标之后,投资者对于市场信息的反应偏差明显减小,说明投资者情绪是造成我国投资者对于市场信息出现过度反应和反应不足的重要原因.我国投资者应该树立起良好的投资意识和心态,避免潜在的投资损失.     

Investment decisions: The trade-off between economic and environmental objectives

While there are broader socio-political, psychological, and structural factors that influence investment decisions (see Harris et al., 2016), in line with the critical approach, this study provides an empirical insight into the notion that financialization, specifically the tendency to prioritise economic over environmental objectives, has a strong bearing on how managers view investment trade-off decisions in relation to sustainability issues. The study empirically investigates this notion by examining the investment trade–off preferences of Australian managers in relation to three decision attributes – economic outcomes (i.e. financial returns), environmental impact (i.e. carbon emissions) and stakeholder pressure to consider environmental issues. We use the discrete choice experimental method to quantify the trade-offs between the above mentioned three attributes. In addition, we also investigate the potential effect of three contingency factors on individual's preferences. Specifically, at the organisational level, we explore the effects of financial and environmental rewards and at the individual level, we explore the effect of environmental consciousness. In line with the financialization hypotheses our results indicate that managers prioritise financial returns over carbon emissions and stakeholder pressures with the preference for financial returns found to be positively associated with rewards for financial performance. However, in line with the pragmatic approach and despite the overall dominance of financial returns, there is evidence that manager's focus on financial returns can be influenced, with the preference for financial returns negatively associated with rewards for environmental performance and environmental consciousness. In addition, while stakeholder pressure was not found to be associated with any of the three contingency factors and, manager's emphasis on carbon emissions was not associated with financial rewards, manager's emphasis on carbon emissions was found to be positively associated with both rewards for environmental performance and environmental consciousness. Therefore, our findings suggest that corporate management have an important role to play, both in respect to the design of performance rewards systems and the recruitment of environmentally conscious managers, in order to promote the sustainability agenda.     

信用风险模型的贝叶斯改进研究

基于小样本数据和外部先验信息,本文运用贝叶斯(Bayes)估计量来改进信用风险模型的违约预测力。同时,运用中国上市公司财务数据,分别对贝叶斯估计量和标准Logit估计量进行了模拟估计,并通过统计量AUC值和布莱尔分数(Brier Score)对其预测精度进行比较。结果表明,贝叶斯估计量具有更高的预测精度和稳定性。     

预测中国宏观经济变量:专家与模型的组合预测

本文使用组合预测方法,探究以“朗润预测”为代表的专家预测以及计量模型对于中国宏观经济变量的预测效果,并研究对不同预测进行组合预测是否有助于改进预测效果。本文发现,对我国CPI和GDP的增长率,专家预测效果总体上优于模型预测。从原因看,一方面,专家在预测时已经考虑了计量模型的预测信息;另一方面,在经济出现“拐点”的时期,专家通过对实际经济环境和政策的把握,得出更准确的经济预测。组合预测有助于提升预测精度,对专家预测进行组合得到的预测效果优于大多数的专家预测,“模型—专家”组合预测的效果也优于所有的模型和大部分专家预测。     

个人信用风险评价系统的统计量表法

本文围绕信用风险统计量表构建的评价测算系统,概要阐述其构造方法与系统运行机理,对其中基本数据结构与算法体系作出明确描述,并对系统开发设计要点给予解析说明。     

中国的通货膨胀:外部冲击抑或货币超发——基于贝叶斯向量自回归样本外预测模型的实证

本文运用贝叶斯向量自回归样本外预测模型分析了中国通货膨胀的诱发因素,发现本轮通货膨胀的最主要原因是近年来中国货币过度发行,而外部冲击则是次要原因。在外部冲击中,国际食品价格变化对中国通货膨胀的影响较大,国际石油价格变化影响较弱。Diebold-Mariano(D-M)检验也表明包含货币供应量的贝叶斯向量自回归样本外预测模型对通货膨胀的预测能力要高于其他模型,开放经济模型对中国通货膨胀分析有较好的适用性。     

金融企业的服务品牌内化研究

服务品牌内化研究是当前服务品牌研究领域的热门话题。金融企业通过构建基于机制设计下的服务品牌内化模型,能够有效地确定目标市场,进行品牌定位,实现品牌承诺和价值主张,激发员工参与行为,培养客户的忠诚度,实现获利战略目标。论文在研究前人成果的基础上,创新性的提出了三维客户价值体验公式、服务品牌构建路径、服务品牌内化六力假设模型、基于机制设计理论的服务品牌内化模型,为下一步的品牌内化研究提供了初步的理论模型,并对中国金融企业,以及其他企业服务品牌建设有着较高的实践意义。     

Applying the biological evolution metaphor to technological innovation

A synthetic theory of evolution is taken as representing the metaphor for the process of innovation. The model is employed to highlight major characteristics of changes in technological innovation and in the time phasing of industrial inventions and innovations. Analysis at the level of the industrial sector is used as a heuristic example of the metaphor, with a focus on innovations in the car industry. Forecasting future products is seen as related to materials requirements, primary human needs and the role of the service sectors.     

运用贝叶斯网络量化和控制商业银行操作风险——一个基于实际业务流程的例子

操作风险量化是为降低和控制风险服务的。运用贝叶斯网络分析量化操作风险并改进控制,对提升商业银行的操作风险管理水平是一条有效途径。论文以我国银行的一个典型业务—远期结售汇为例,研究了实践中建立和运用贝叶斯网络来估计操作风险发生频率的具体方法。以流程分析和映射为基础,阐述了风险映射与节点识别、网络结构建立、网络节点描述、节点赋值的实施步骤,并说明了利用贝叶斯网进行因果推理和诊断推理的方法。     

基于贝叶斯网络的上市证券公司风险预警模型研究

上市证券公司的风险预警模型能够为政府监管、证券公司稳健发展以及投资者研判提供依据。以上市证券公司风险管理指标体系为基础,利用贝叶斯网络方法以及支持向量机、随机森林和多项Logit模型分别建立风险预警模型进行比较,并在实证中针对上市证券公司的不平衡数据特征,用 SMOTE抽样对数据进行预处理。最终实证表明：从平均准确率和标准差两个角度比较,SOMTE抽样增加了贝叶斯网络的预测效果,机器学习方法要优于多项Logit模型,贝叶斯网络方法效果最佳。     

Criteria of systems thinking

In science, the framework of systems theory—especially as developed over the past two decades—seems to be the ideal framework to express the emerging ecological paradigm. This article addresses the question: what is systems thinking—and more generally, holistic or ecological thinking—in modern science? The author identifies three key aspects of systems thinking that are characteristic in all the sciences. In presenting these aspects, the transition from the old to the new paradigm for each aspect is emphasized.     

Impact of intelligent decision aids on expert and novice decision-makers' judgments

Businesses have invested tremendous resources into intelligent decision aid development. A good match between user and aid may improve the expert decision‐maker's decision quality. However, novices may be prone to poorer decision‐making if intelligent decision aids are more expert than the user. The present paper provides an empirical test of the impact of decision aids on subjects with differential expertise levels. The results support the contention that intelligent decision aids aggravate bias in novices’ decision‐making but mitigate bias in experts’ decision‐making processes. Intelligent decision aids may be best viewed as complements to expert decision‐makers during complex problem analysis and resolution.     

基于贝叶斯SV模型的通货膨胀水平与不确定性关系研究

针对我国通货膨胀水平与不确定性的时变性特征,分别建立了随机波动均值模型和非对称随机波动均值模型,在MCMC稳态模拟的框架下研究了我国通货膨胀水平与不确定性的动态关系。研究结果表明:我国通货膨胀不确定性中具有明显的持续性特征,并且通胀水平中虽然不存在与金融资产价格运动类似的杠杆效应,但是正向冲击增加了经济行为主体对未来不确定性的预期,由此将导致明显的\"示范效应\"和\"追涨效应\";特别是风险溢出系数的贝叶斯估计为正,反映了通胀不确定性对通胀水平的正向影响作用,说明我国目前的货币政策框架中含有相机抉择的成分因素。