会计估计的准确性、行业共识信息与个体投资者的决策

会计信息在投资者的投资决策过程中发挥着十分重要的作用,其质量直接影响着投资者的判断和决策.会计估计在提高会计信息相关性的同时,也为公司管理层提供了盈余管理的空间.本文实验检验了对会计估计的准确性进行事后披露这一机制是否有助于个体投资者做出正确的判断和决策,以及行业共识信息对这一机制发挥作用的影响.研究发现:(1)事后披露会计估计准确性的信息只有通过行业共识信息的辅助才能有效发挥作用,即只有在两者的共同作用下,个体投资者才能够正确识别会计估计准确的原因,也才能够进行正确的归因,并做出正确的判断和决策;(2)投资者对会计估计的准确性会产生不同的归因,投资者的归因进一步影响了其对管理层评价,而对管理层的评价影响了其对公司市盈率的评价,对公司市盈率的评价进一步影响了投资者对其投资可能性的判断.     

REPORT FREQUENCY AND MANAGEMENT DECISIONS

There is no theory to prescribe how frequently accounting reports should be issued for management decisions; indeed, one research study could not find evidence that frequency of reports is a variable in the decision process. Accounting reports are discrete aggregations from continuous processes, and frequency affects information content of reports. If frequency affects information, it therefore must be a variable in the decision process. This research investigated the question of whether the report frequency had any effect on evaluations made from accounting reports issued on different intervals. Evidence is presented to support the conclusion that frequency is a factor in the decision process and that decision behavior is affected by the frequency of reports. This report merely demonstrates the existence of the report frequency variable; much more research is necessary to control the variable for optimal system design.     

Accounting Performance and Capacity Investment Decisions: Evidence from California Hospitals

Capacity decisions involve trade‐offs between the cost of capacity and the opportunity costs of lost sales. Accounting researchers posit that accounting performance provides sufficient information about these trade‐offs and thus can be used to formulate simple rules to assist capacity decisions. Empirical research has not examined the role of accounting information in capacity investment decisions at the department level in a multiproduct firm in the presence of social costs. Empirical analyses using department‐level data from California hospitals for the period 1998–2005 show that hospitals are more likely to make capacity investments in departments with high accounting performance. However, in the presence of demand variability, the association between accounting performance and capacity investment is attenuated because of the resulting increase in noise in accounting performance measures. Thus, the weight on accounting performance as a decision tool for capital investments reduces when there is demand variability. Another factor that reduces the weight on accounting performance is capacity utilization. Higher capacity utilization can lead to turning away or rerouting of patients to other hospitals and negatively impacts reputation and quality of care, which increases the hospital's social costs. Hence, hospitals do not require high accounting performance before investing in a department with high capacity utilization. This empirical evidence of the role of accounting performance in capacity investment decisions fills a gap in the capacity investment literature and furthers our understanding of the interactions between accounting performance and the operational determinants of firms’ capacity investment behavior.     

基于产品生命周期的多阶段剩余收益项目决策模型

剩余收益模型（Residual Income Model,RIM）是评估公司权益价值的经典模型,特别地,奥尔森系列剩余收益模型由于可以利用历史财务与会计数据而得到广泛运用。本文在一般剩余收益模型的基础上,运用规范研究、逻辑推理等方法,基于产品生命周期理论,即项目处于产品生命周期的不同阶段时,其净资产收益率不同,在增长期的净资产收益率持续上升,衰退期的净资产收益率持续下降,而成熟期的净资产收益率则围绕行业平均水平波动,从理论上就项目投资价值的评估构建了多阶段剩余收益项目决策模型,并就所构建的多阶段剩余收益项目决策模型进行参数赋值分析。研究结果表明该新构建的决策模型具有较好的理论和运用价值,可以作为一种有效的项目投资决策模型。本文的研究一是拓展了剩余收益模型的应用,从主要用于对公司权益价值的估值拓展至对项目投资决策的评估;二是有利于寻求项目投资决策的价值最大化。     

Strategic Decisions of New Technology Adoption under Asymmetric Information: A Game‐Theoretic Model*

In this paper we explore strategic decision making in new technology adoption by using economic analysis. We show how asymmetric information affects firms' decisions to adopt the technology. We do so in a two‐stage game‐theoretic model where the first‐stage investment results in the acquisition of a new technology that, in the second stage, may give the firm a competitive advantage in the product market. We compare two information structures under which two competing firms have asymmetric information about the future performance (i.e., postadoption costs) of the new technology. We find that equilibrium strategies under asymmetric information are quite different from those under symmetric information. Information asymmetry leads to different incentives and strategic behaviors in the technology adoption game. In contrast to conventional wisdom, our model shows that market uncertainty may actually induce firms to act more aggressively under certain conditions. We also show that having better information is not always a good thing. These results illustrate a key departure from established decision theory.     

Accounting, strategy and AMT investment

One strand in the current debate on AMT investment emphasises technical aspects of investment appraisal. Another calls for a broader focus on wider decision-making processes and strategic considerations. This paper seeks to merge both sets of concerns. It uses two empirical studies of AMT decisions in a number of companies. The first demonstrates specific linkages between manufacturing strategies and financial justifications. The second explores ways in which connections between finance and strategy are constructed and how they are understood and evaluated by decision-makers. We conclude that AMT proposals succeed by linking accounting information to strategic considerations throughout the investment decision process.     

A generic accounting model to support operations management decisions

Information systems are generally unable to generate information about the financial consequences of operations management decisions. This is because the procedures for determining the relevant accounting information for decision support are not formalised in ways that can be implemented in information systems. This paper describes a formalised procedure, which is based on the following theoretical propositions: (i) cost behaviour is described on the basis of a company's contracts for purchasing and selling resources, and (ii) hierarchical relationships between decisions are recognised, because some decisions have to be made earlier than others. Earlier decisions determine the feasible alternatives for later decisions (e.g. through constraints in available production capacity or components), and the plans that supported the earlier decisions serve as instructions for later decisions. The procedure can be implemented in information systems to provide accounting information in case later decisions deviate from these instruc tions (within the limits of the real-world constraints) because new information becomes available.     

Top Management Team Members’ Decision Influence and Cooperative Behaviour: An Empirical Study in the Information Technology Industry

Organizational leadership is generally distributed between the chief executive officer (CEO) and the top management team (TMT) members. Building on this observation, we present an empirical investigation of the cues for CEOs to delegate decision‐making influence to particular TMT members. In the literature, explanations both based on expertise and driven by similarity are described. In this study, we reconcile both explanations by examining the moderating role of the TMT's level of ‘cooperative behaviour’ (collaboration and information exchange). We analyse when and in what circumstances TMT members’ expertise and similarity to the CEO regarding his/her functional background and/or locus‐of‐control predict their decision‐making influence. We postulate that TMT cooperative behaviour will advance the effect of expertise on TMT members’ decision influence but impede the effect of similarity to the CEO. Our hypotheses are tested on a data set of 135 TMT members from 32 Dutch and Belgian information technology firms. Overall, we find that our proposed research model is confirmed for technology‐oriented decisions. Furthermore, we draw exploratory conclusions about the effect of TMT cooperative behaviour on the systematic distribution of decision influence in TMTs.     

Organizational Computing as a Facilitator of Operational and Managerial Decision Making: An Exploratory Study of Managers' Perceptions*

Much of the current knowledge pertaining to information technology (IT) and decision making is based on decades old technologies that revolved around a central computing function and application-specific systems. The purpose of this research is to examine the IT decision-making relationship within the emerging organizational computing (OC) environment permeated by spontaneous utilization of both application-and nonapplication-specific computing and communication technologies. Specifically, this study seeks to explore managers' perceptions of the emerging OC environment as a facilitator of their decision-making activities. To achieve a higher level of clarity than previous works, a two-dimensional research framework is developed with the IT dimension consisting of computing and communication, and the decision-making dimension differentiated between operational and managerial decisions. A survey instrument was constructed that measured the computing and communication dimensions of information technology use and their perceived effects upon operational and managerial decisions. The major findings of the study confirmed that managers recognize the value of general, nonapplication-specific information technologies in decision making, and that this recognition is highly associated with how intensively these information technologies are used. Additionally, it was found that the two dimensions of IT differ in their relationships to decision making, and that IT usage relates to managerial decisions differently than operational decisions. These study findings have significant implication for practice and research, especially in the context of information resource management in which the primary purpose of the IS function is the delivery of general information service to users rather than the development of specific IS applications.     

CAPACITY AND PRODUCTION DECISIONS IN STOCHASTIC MANUFACTURING SYSTEMS: AN ASYMPTOTIC OPTIMAL HIERARCHICAL APPROACH

We present a new paradigm of hierarchical decision making in production planning and capacity expansion problems under uncertainty. We show that under reasonable assumptions, the strategic level management can base the capacity decision on aggregated information from the shopfloor, and the operational level management, given this decision, can derive a production plan for the system, without too large a loss in optimality when compared to simultaneous determination of optimal capacity and production decisions. The results are obtained via an asymptotic analysis of a manufacturing system with convex costs, constant demand, and with machines subject to random breakdown and repair. The decision variables are purchase time of a new machine at a given fixed cost and production plans before and after the purchase. The objective is to minimize the discounted costs of investment, production, inventories, and backlogs. If the rate of change in machine states such as up and down is assumed to be much larger than the rate of discounting costs, one obtains a simpler limiting problem in which the random capacity is replaced by its mean. We develop methods for constructing asymptotically optimal decisions for the original problem from the optimal decisions for the limiting problem. We obtain error estimates for these constructed decisions.     

混合分销渠道结构下短生命周期产品供应链库存策略分析

随着竞争的加剧,产品生命周期日渐缩短。信息和网络技术的不断进步,使得网络作为一种特殊的分销渠道出现。传统分销渠道和网上直销渠道并存的混合分销渠道结构给理论研究和管理实践提出了新的挑战,本文针对混合分销渠道结构下短生命周期产品供应链,运用报童问题的框架,分析了两种不同运作模式下生产商和零售商库存策略,并通过数值实验研究了需求不确定性对生产商和零售商最优库存策略的影响。最后,根据数值实验的计算结果,总结了本研究的管理启示。     

Financial reporting in Europe: Prospects for research

This paper is a commentary on the future of financial reporting in Europe and on how research into accounting issues can be relevant to policy makers. Combining scholarship in accounting with scholarship in management can offer insight into national and global issues where accounting communicates information that affects managerial decisions at the microeconomic level and political decisions at the macroeconomic level. The paper cites examples of recent research in financial reporting and points to the current work plans of leading policy makers to illustrate the potential for researchers to influence policy directions. The context of financial reporting, nationally and globally, and the data available in the public domain, provide continued opportunities for researchers investigating accounting issues in the private sector and the public sector.     

新创企业高管团队的团队过程与战略决策绩效 ——认知的调节作用

新创企业的成败很大程度上取决于战略决策绩效,具有决策权力的高管团队在创业情境下的认知和行为过程对战略决策绩效具有重要影响。本文结合创业研究和高管团队研究的现有成果,以122家新创企业为研究对象,从内部团队过程和外部团队过程两个维度考察高管团队的团队过程对战略决策绩效的影响,并从认知的视角分析新创企业高管团队认知需要和认知能力对团队过程与决策绩效关系的调节作用。研究结果表明,新创企业高管团队的内部团队过程和外部团队过程与决策的质量和满意度均有显著的正相关关系,且认知需要和认知能力对这种关系具有调节作用,在认知需要和认知能力较高的情况下,内、外部团队过程对决策质量和满意度的正向影响更强。     

基于投资跳扩散的研发项目投资决策研究

为解决由于技术创新使得研发项目的投资发生泊松跳跃时的投资决策问题,本文针对研发项目的投资不确定性,建立了基于跳扩散过程的研发项目投资决策模型,并在传统跳扩散模型中引入了新的变量-经营成本,侧重分析了技术溢出和吸收能力对项目投资临界值的影响。最后,通过算例对各个参数进行了灵敏度分析。     

互动公平、委员会决策程序公平与员工决策承诺:基于公平启发理论与不确定管理理论的实证研究

借助层级团队形式制定决策,决策者能激发员工的决策承诺,确保决策的有效执行。以委员会作为决策者的层级团队为例,本文探讨了以下问题:当存在个体对自身胜任力的自信、专用性人力资本投资这两个因素的影响时,互动公平与委员会决策程序公平效应及它们之间的交互效应会发生什么变化?引入公平启发理论与不确定管理理论,本文假设并检验了上述四个因素如何交互作用于员工决策承诺。以两家大型商业银行信贷业务人员为研究对象,实证研究表明:(1)自信和专用性人力资本投资对委员会决策程序公平效应有着显著调节作用,但它们对互动公平效应的调节作用不显著;(2)当存在自信和专用性人力资本投资的影响时,较强的互动公平与委员会决策程序公平之间的交互效应更稳定一些,而较低的互动公平感知与程序公平之间的交互效应在方向上发生变化。本文有助于管理者理解"公平何时能引致员工合作"这一问题,帮助其更好地把握决策过程以获得员工对其决策的支持。本研究的假设完全基于公平启发理论(FHT)和不确定管理理论(UMT)的理论逻辑做出,实证结果与FHT和UMT的理论预测以及已有实证研究结果相一致,这意味着本研究具有较高可信性和可靠性,能为进一步理论探索提供了比较坚实的基础。     

债务容量与成长期权关系研究

本文利用期权博弈方法,探析投资成长期权如何影响公司债务融资决策问题。在不确定条件下,综合考虑利率、税率、债息和债务的期限结构这些影响融资和投资的重要因素,构建期权博弈理论模型,确定企业的最优债务容量,并运用数值方法给出了债务容量与投资成长期权的回报率之间是非线性的"U"形关系的结论。研究表明,当投资成长期权的回报率较低时,债务容量随着投资成长期权的回报率增加而债务容量减少;当投资成长期权的回报率达到较高水平时,债务容量随着投资成长期权的回报率增加而债务容量增加。从而给出了关于债务容量与投资成长期权之间的内在关系的新理论解释。     

A Simulation of Partial Information Use in Decision Making: Implications for DSS Design

Information matrices are often the output produced by a decision support system. These matrices are a common method for expressing a decision situation under different decision-making scenarios. The decisions involved in designing a decision support system to generate the information matrix are important and involve several cost and benefit components. A designer needs guidance in making effective design decisions in this context. Such guidance can be provided by considering the relationships among specific design decisions, costs, and benefits. The general objective of this study is to provide a comprehensive framework for this purpose. This study is the first to develop and present a comprehensive cost-benefit framework for evaluating design decisions for a variety of scenarios. The specific objective of this research is to provide guidance regarding the number of available information dimensions to incorporate in a computer-based decision aid. Simulation experiments are conducted with a completely specified model based on the cost-benefit framework (including needed assumptions) to evaluate how many information dimensions to include for a specific information matrix size to achieve a balance between information use costs and decision quality. Based upon extensive simulation analyses for a hypothetical decision maker, the practical guideline found for designers is to include only the top half of the relevant information dimensions in any specific decision support system. Over a large number of repeating choice decisions, the savings in cognitive effort and information gathering costs clearly offset relatively minor losses in decision quality.     

基于一致性度量的概率模糊语言多属性群决策方法

人们通常习惯用语言术语来表达他们的偏好，因此概率型语言术语集（Probabilistic Linguistic Term Set，PLTS）在决策过程中有着十分重要的作用。目前PLTS的研究刚刚起步，有关PLTS的相关研究没有关注到一致性度量的问题，对于PLTS的多属性群决策方法有待进一步研究。首先，给出了一种新的PLTS的集结方法，并且在已有的PLTS可能度公式的基础上，构建了PLTS的相似度量方法，在此基础上，进一步提出了基于PLTS一致性度量的多属性群决策方法。该方法在各决策者权重未知的情况下，考虑到各决策者之间的一致性。首先，定义PLTS的一致性度量公式，确定决策者权重；并根据PLTS的集结方法，集结各决策者的评价信息；最后，利用可能度公式对PLTS进行排序。通过案例分析验证了该方法的可行性和优越性。     

USING SENSITIVITY ANALYSIS TO EVALUATE MATERIALITY*

A large body of the published research in financial accounting provides strong and persuasive evidence on the association between accounting numbers and stock prices but falls short of drawing any implications about accounting policies on measurements or on reporting. Attempting to go beyond association the author of this paper provides an application of a possible methodology for evaluating materiality of accounting measurements in a given decision situation. The methodology employs discriminant analysis in which the sensitivity of the discriminating model to the changes in mean earnings per share provides a decisions reaction scale and shows that a change in mean earnings per share equal to or less than 10% does not significantly affect the prediction. The validity of the results would depend on the correspondence between this model and the behavior of decision-makers. However, in situations such as the one chosen here, in which an investor's decision-making process cannot be normatively structured, appropriate statistical methods effectively can be utilized to describe the process.     

A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach

Large-scale multinational manufacturing firms often require a significant investment in production capacity and extensive management efforts in strategic planning in an uncertain business environment. In this research we first discuss what decision terms and boundary conditions a holistic capacity management model for the manufacturing industry must contain. To better understand how these decision terms and constraints have been employed by the recent model developers in the area of capacity and resource management modelling for manufacturing, 69 optimisation-based (deterministic and stochastic) models have been carefully selected from 2000 to 2018 for a brief comparative analysis. The results of this comparison shows although applying uncertainty into capacity modelling (in stochastic form) has received a greater deal of attention most recently (since 2010), the existing stochastic models are yet very simplistic, and not all the strategic terms have been employed in the current model developments in the field. This lack of a holistic approach although is evident in deterministic models too, the existing stochastic counterparts proved to include much less decision terms and inclusive constraints, which limits them to a limited applications and may cause sub-optimal solutions. Employing this set of holistic decision terms and boundary conditions, this work develops a scenario-based multi-stage stochastic capacity management model, which is capable of modelling different strategic terms such as capacity level management (slight, medium and large capacity volume adjustment to increase/decrease capacity), location/relocation decisions, merge/decomposition options, and product management (R&D, new product launch, product-to-plant and product-to-market allocation, and product phase-out management). Possibility matrix, production rates, different financial terms and international taxes, inflation rates, machinery depreciation, investment lead-time and product cycle-time are also embedded in the model in order to make it more practical, realistic and sensitive to strategic decisions and scenarios. A step-by-step open-box validation has been followed while designing the model and a holistic black-box validation plan has been designed and employed to widely validate the model. The model then has been verified by deploying a real-scaled case of Toyota Motors UK (TMUK) decision of mothballing one of their production lines in the UK after the global recession in 2010.