Multiple criteria decision making for maritime investment policy in the developing countries

This model for multiple criteria decision making enables one to select an optimal investment policy for developing the marine industry in developing countries. The model is composed of: the mathematical model of national economy (LP model) for optimizing an investment scheme under economic and technological constraints; the model of I-O analysis for estimating the change of industrial structures induced by the investment; and the decision making model to which the results of the preceding models are fed back so as to enable the policy planner to select a feasible policy based on his own multiple criteria such as the value of GDP growth rate, international payments, unemployment rate, etc. Due consideration is paid in this study to the role of the marine industries, e.g. shipping and ports, which can be said to be the pivot of economic development in a developing country in connection with its foreign trade policy. A case study is carried out to verify this hypothesis.     

Comparing methods for weighting decision criteria

Several metbods have been proposed to weight decision criteria. In this field study a decision group, like that used by public agencies, was formed to establish project priorities. The decision group used a variety of criteria weighting methods to study how these methods influence the magnitude of the weights assigned by members of the decision group. Direct criteria weighting methods (scaling, rank-weight, point assignment and odds procedures) and an indirect approach (weights derived from hypothetical projects) were considered. The study compared the methods in terms of the magnitude of the weights assigned, the variance in weights among members of the decision group, and the similarity of the decisions based on weights assigned by each method. The time to apply each method and the preferences of the decision makers were also determined. The linear rating scale that defined the meaning of scale increments, called an ‘anchored ratin scale’, was found to be favorably received and efficient and led to the most defensible decisions.     

Setting investment criteria for government and industry

This article follows that by the same author on using scenarios to develop strategies which appeared in Long Range Planning, 18 (2), 30–37 (1985). This second paper concentrates on the relationship between long-term objectives, criteria and strategies, as they may be formulated by government and industry. A logical framework is presented in which criteria emerge as essential variables in a dynamic process of strategy development.     

社会保险与家庭金融风险资产投资

 当公司违规时对CEO及时有效地进行变更是董事会的重大决策之一,董事会作为上市公司监督和决策的重要机构,其独立性至关重要。董事会独立性是公司治理的灵魂,已有研究将董事会独立性作为一种形式上的独立性,忽略了可能影响董事会职能发挥的其他社会因素,如董事会成员与CEO非正式关系和人口统计学特征的匹配程度,因此有必要进一步探讨董事会社会独立性。        采用社会网络和社会认同理论,从董事会监督职能有效性发挥角度,创新性地构建包含认知和关系双层的董事会社会独立性测量指标,以2011年至2014年沪深A股发生CEO变更的上市公司及其配对公司为样本,运用probit模型实证研究不同情景下,当公司出现违规行为时,董事会社会独立性对CEO变更的影响效应。        研究结果表明,①董事会社会独立性越高,违规公司的CEO越容易发生变更行为,董事会成员与CEO关系亲密以及人口统计学特征相近所形成的较高的契合度使董事会无法客观公正地评判和监督CEO的业绩表现;②董事会社会独立性效应的发挥与上市公司的所有权性质和业绩表现有关,在民营企业和劣绩公司,董事会社会独立性的调节效应更显著;③良好的制度环境等外部治理机制为董事会社会独立性的效用发挥提供了保障,董事会社会独立性只有在外部治理较好的情形下才会影响违规公司的CEO变更。        董事会社会独立性作为独立性研究的拓展,具有重要的理论意义和现实意义。研究结果表明提升公司治理有效性,不仅在于保持结构的独立,还需要提升董事会的社会独立性。公司应严格把控“关系型”和“相似型”CEO,同时还应创造独立良好的外部治理环境,保障董事会更好地发挥监督职能。     

社会保险与家庭金融风险资产投资

社会保险是否影响家庭在金融风险资产中的投资决策呢?本文使用两期家庭最优决策模型得到的理论分析结果表明,社会保险不仅能够提高家庭在风险资产中的投资广度和深度,而且对于不确定性更大、风险承受更强家庭的影响更为显著.基于省级层面得到的宏观实证检验结果和基于2011年家庭金融调查数据得到家庭层面的微观实证检验结果都支持了上述理论结论.本文的发现对于协调社会保险发展和建立多层级金融市场具有很强的政策意义.     

最优保险投资决策

2005年初我国对保险公司直接进入资本市场进行投资开始放开.如何选择最佳的投资策略就成为目前保险公司所面临的难题,而传统的投资模型的诸多不足使得它在实际应用中有很大局限性.讨论的模型克服了传统模型的不足.在该模型中,索赔是一个复合Poisson过程,保险公司可选择与投资期内的安全要求相一致的投资比例.应用最优控制原理求解模型得到了最优投资策略以及有效边界的解析形式,并讨论了承保收益和承保风险对投资策略与有效边界的影响.     

Cybernetic approach to investment decision making

This paper summarizes the results of our research into applications of cybernetic concepts and artificial intelligence techniques to investment analysis: it outlines the philosophy underlying the cybernetic approach to market forecasting and investment selection. This approach is computer oriented—it enables us to automate or program directly the complex judgmental aspects of investment decision making. The cybernetic approach alleviates some deficiencies of conventional statistical methods. Specifically, it (1) explicitly includes the time dimension into investment analysis, (2) is based on methods for decision making under uncertainty rather than risk, (3) yields computationally feasible methods for coping with the high complexity in investment analysis, and (4) yields decisions that are optimal rather than satisficing, i.e. performance of the Cybernetic Investment Decision System (CIDS) gradually improves during its operation through learning from past experience. A simplified CIDS has been implemented and tested in actual investment analysis. The experimental results of these tests indicate that through the cybernetic approach quality of investment decisions can be improved.     

The indifference band in multiple criteria decision problems

A case study of a discrete multiobjective problem using the ‘Indifference Band’ approach is presented. An outranking relation among the various alternatives was obtained and compared with the management's own ranking. It was found that the ‘Indifference Band’ approach can be used in ranking procedures.     

Beyond Markowitz with multiple criteria decision aiding

The paper is about portfolio selection in a non-Markowitz way, involving uncertainty modeling in terms of a series of meaningful quantiles of probabilistic distributions. Considering the quantiles as evaluation criteria of the portfolios leads to a multiobjective optimization problem which needs to be solved using a Multiple Criteria Decision Aiding (MCDA) method. The primary method we propose for solving this problem is an Interactive Multiobjective Optimization (IMO) method based on so-called Dominance-based Rough Set Approach (DRSA). IMO-DRSA is composed of two phases: computation phase, and dialogue phase. In the computation phase, a sample of feasible portfolio solutions is calculated and presented to the Decision Maker (DM). In the dialogue phase, the DM indicates portfolio solutions which are relatively attractive in a given sample; this binary classification of sample portfolios into ‘good’ and ‘others’ is an input preference information to be analyzed using DRSA; DRSA is producing decision rules relating conditions on particular quantiles with the qualification of supporting portfolios as ‘good’; a rule that best fits the current DM’s preferences is chosen to constrain the previous multiobjective optimization in order to compute a new sample in the next computation phase; in this way, the computation phase yields a new sample including better portfolios, and the procedure loops a necessary number of times to end with the most preferred portfolio. We compare IMO-DRSA with two representative MCDA methods based on traditional preference models: value function (UTA method) and outranking relation (ELECTRE IS method). The comparison, which is of methodological nature, is illustrated by a didactic example.     

双重随机不确定条件下的一次性容量扩展投资

考察在未来市场价格和新增容量利用率双重不确定条件下,一次性容量扩展项目投资的最优时机选择问题.应用实物期权的相关理论和方法,建立了一个以投资期权价值最大化为目标函数,以期望第一触点时间为决策变量的项目投资决策模型,并设计了基于Riskoptimizer软件包的仿真优化算法.最后的仿真算例表明了双重随机不确定因素对容量扩展项目最优投资时机选择的定量影响.     

基于序列投资的汽车项目投资决策模型

汽车项目投资具有投资大和较高的不确定性特点,一般分阶段进行,可以视为一个序列投资.多个投资阶段之间存在着相互影响,前一阶段的投资应考虑到后续各阶段投资的可能性.以汽车项目投资为背景,运用二叉树决策方法建立了多阶段的序列投资评价模型,并应用实物期权理论对序列投资中各阶段可能创造的价值进行了分析.通过构建基于序列投资评价的汽车项目投资决策模型,可以对汽车企业投资进行评价,有助于做出有效的决策.     

内部控制监督最优投资分配模型及决策研究

内部控制监督是现代企业改善经营管理、降低重大内控缺陷发生可能性的重要措施． 本文构建了一个企业内部控制监督的最优投资分配模型． 该模型提出了内部控制缺陷率和流程可靠性两个概念,认为增加内部控制监督的投资可以降低内部控制缺陷率,从而增加流程可靠性． 本文借鉴了工程领域的可靠性理论,定义了内部控制监督投资的效用函数,以企业效用最大化为决策目标,考虑在投资预算额一定的情况下资金在各个业务流程中的分配策略． 模型分析表明,以串联方式连接的流程在增加内部控制监督投资时,投资额的大小与该流程实际发生 风险的可能性相关,实际发生风险的可能性越大,投资额与该流程内控强度的乘积就越大． 而在并联系统中,流程投资额的大小与各流程的内控强度有关． 但当各个流程的内部控制强度相等时,并联系统的最优投资额在各流程间平均分配时系统的效用最大． 此外,本文还证明了并联系统的效用高于串联系统．     

不确定性、学习与新技术序列投资决策

以不同性质不确定性与其解决方式(学习)和效率对投资价值的影响为切入点,研究新技术序列投资行为背后的决策机制与路径.在现有研究基础上,引入企业内部学习的异质性特征,把技术不确定性的解决效率分解为学习能力、累积学习效应与边际学习效应3个层次进行讨论.运用实物期权方法构建包含学习效应的新技术序列投资决策模型,并得到最优决策规则,通过数值方法对不同参数进行比较静态分析,并阐述结果的经济与管理涵义.     

Multiple criteria decision analysis of treatment and land-filling technologies for waste incineration residues

In this paper, we present a real-world case realized in Switzerland on behalf of the federal agency in charge of the waste policy. The incineration of urban wastes generates hazardous residues that need specific treatment and/or land-filling technologies. The variety of local situations and appraisals led to the choice of very different solutions. Moreover, proponents were keen to propose new technologies. The purpose of this study was to provide the background for a national policy that would apply to all future projects.     

不确定性和动态能力互动下企业投资竞争决策

环境不确定性和动态能力的互动对企业国际化投资竞争策略和时机选择有着重要影响．在考虑企业先后动优势和相对能力综合影响以及内外生环境不确定性差异冲击的基础上,构建了不完全竞争市场的投资策略决策模型,并结合跨国公司在华投资实践,分析了初始能力、动态能力、先后动优势以及内外生环境不确定性对企业间投资竞争策略的均衡条件和投资时机决策的影响． 研究结果表明,先后动优势和相对能力共同决定了企业间投资竞争策略均衡; 内生不确定性和外生不确定性对竞争策略均衡产生反向冲击,对抢占时机和投资时间间隔决策却产生一致影响．     

Stock screening with use of multiple criteria decision making and optimization

A new method for the stock ranking based on the multiple criterion decision making and optimization is proposed. Two general criteria are used in the analysis. The first of them is based on the financial indices and may be treated as the criterion of firm's “health” or its financial performance. The second one is the two-criteria performance of firm based on the stock prices. It represents the firm's market success. The method rests on the selection of the stocks with a great correlation of the firm's financial performance and its market success. The local criteria are built in the form of the membership function of corresponding fuzzy subsets. Two different strategies for stock ranking and three most popular methods for local criteria aggregation are compared. As the example the values of financial rations and prices from database comprising the data of 162 firms from subsector of the biotechnology of US economy were used. It is shown that the proposed method makes it possible to select a small group of “good” stocks characterized by a great coincidence of firm's financial performance and its market success. The method rejects from the consideration all the “unsafe” firms, i.e., such ones that their market success is based rather on the public relations, rumors and other rather unreliable information. The method is addressed to those who prefer to select for a portfolio only the firms which demonstrate the closeness of their overall financial performance in the past year and success in the Stock Exchange in the following year.     

An analytic hierarchy process based simulation model for entry mode decision regarding foreign direct investment

A methodology is developed for ranking entry mode alternatives encountered by individual firms considering foreign direct investment (FDI). The methodology deals with the risks and uncertainties related to FDI. The analytic hierarchy process (AHP) is used to solve the multiple criteria decision-making problem using input from a firm's management. A simulation approach is incorporated into the AHP to handle the uncertainty considerations encountered in an FDI environment. The uncertainties include: (1) uncertainty regarding the future characteristics of the FDI decision making environment, (2) uncertainty associated with the decision maker's judgment regarding pairwise comparisons necessitated by the AHP.