基于灰色关联度的多目标电力建设工程投资决策研究

项目投资决策系统是一个典型的灰色系统,它具有灰色系统信息部分不确定性的特点。将灰色系统理论与层次分析法（AHP）进行有机地结合,用加权灰色关联度分析方法建立模型并计算判断矩阵,为决策者提供一种有效的决策方法。应用灰色关联分析方法处理电力建设项目投资决策问题,考虑不同因素的重要程度,运用AHP方法对其进行赋权,根据得到的加权灰色关联度值的大小对备选方案进行优选,使电力建设项目投资方案决策过程更具有科学性。     

Economic impact analysis of inland waterway disruption response

Navigable inland waterways connect inland ports with the global supply chain by providing a low-cost, reliable, and environmentally friendly freight transportation mode. In this article, we present the results from a simulation-based approach that estimates the potential economic impacts of inland waterway disruption response. Predicting economic impacts of inland waterway disruption response enables system stakeholders to increase their preparedness and potentially reduce economic losses. Our approach is implemented on an illustrative case study of the McClellan–Kerr Arkansas River Navigation System. The approach is generalizable to navigable inland waterways throughout the United States to support economic resilience of these systems.     

A COMPARISON BETWEEN TWO MULTIATTRIBUTE DECISION METHODOLOGIES USED IN CAPITAL INVESTMENT DECISION ANALYSIS

Two multicriteria decision methodologies applied to evaluating capital investments are the Analytic Hierarchy Process (AHP) and the Non-Traditional Capital Investment Criteria (NCIC) model. In this paper we demonstrate that a mathematical relationship exists between these two models. In-particular, a data set obtained by one method can be mapped into an equivalent data set obtained using the other method. It is suggested that this offers an opportunity of empirically assessing decision makers judgmental capabilities under varying data collection methods. An example problem illustrates the manner in which such comparisons can be made.     

基于粗糙集的银行存货质押业务投资决策研究

针对银行在存货质押业务筛选中缺乏有效方法,将决策粗糙集引入到存货质押业务筛选中,在考虑延迟决策最优投入的情况下,建立了一个基于期望损失最小下阈值和先验概率对比的决策模型。模型中根据投资决策下的收入和支出来确定损失函数,从而确定决策阈值,通过历史数据构建信息表确定先验概率,经阈值和先验概率二者对比,得出银行针对业务的最优决策,算例分析显示模型对银行业务投资决策有一定的借鉴意义。     

A Comparison of Fuzzy Set and Probabilistic Paradigms for Ranking Vague Economic Investment Information Using a Present Worth Criterion

This article introduces an approach for comparing the fuzzy set and probabilistic paradigms for ranking vague economic investment information when a present worth criterion is used. Comparisons are made between the two paradigms by forming a ratio of fuzzy ranking value to probabilistic ranking value for a set of tested economic decision conditions (vague cash flows and interest rates). A multivariable analysis of the comparison ratios indicates the dominance or spread required in the expected present worths of competing alternatives to guarantee consistent decision ranking among the paradigms. Results of the research suggest that probabilistic methods will not rank vague economic investment information the same as fuzzy set methods. As a result, decision makers who use probabilistic methods to model vagueness in human thought (the condition for which fuzzy theory was developed) may obtain rankings inconsistent with those obtained via the fuzzy models. In such cases, if decisions are based on project rankings, then different choices or recommendations are likely.     

Confounding changes in averages with marginal effects: How anchoring can destroy economic value in strategic investment assessments

Profit maximization requires that decision makers assess marginal profits. We demonstrate that decision makers often confound marginal profits with changes in average profits (e.g., changes in return‐on‐investment). This results in systematic deviations from profit maximization where decision makers forgo profit‐enhancing investments that reduce average profits or engage in loss‐enhancing investments that decrease average losses. In other words, average profit becomes an anchor by which new investments are assessed. We conduct two decision‐making experiments that show this bias and demonstrate it is pronounced when average profit data are accessible or task‐relevant. Moreover, we find within‐subject effects across experiments, which helps demonstrate the mechanism that invokes the bias. Copyright © 2013 John Wiley & Sons, Ltd.     

Decision support system to design feasible high-frequency Motorways of the Sea: A new perspective for public commitment

ABSTRACT

The implementation of Motorways of the Sea (MoS) within the framework of European Union aid programs experiences a period of relative stagnation. This article analyzes the suitability of current short-term nonrepayable subsidy policy and develops a decision support system (DSS) that allows a medium- and long-term feasibility analysis of MoS proposals. One significant conclusion drawn from the application of the proposed DSS to a prototypical high-frequency MoS provides that the period of initial losses prior to achievement of both modal shift and accounting profits might last 10 years. Moreover, the entire duration of the period that includes prior objectives as well as the recovering of initial losses might reach 25 years. Therefore, existing schemes of public–private collaboration should be redefined. To this end, the proposed DSS also contributes to envisioning a spectrum of possibilities for private–public collaborations schemes, as opposed to public–private dichotomy of partnerships.     

Supply chain risk, simulation, and vendor selection

This paper considers three types of risk evaluation models within supply chains: chance constrained programming (CCP), data envelopment analysis (DEA), and multi-objective programming (MOP) models. Various risks are modeled in the form of probability and simulation of specific probability distribution in risk-embedded attributes is conducted in these three types of risk evaluation models. We model a supply chain consisting of three levels and use simulated data with representative distributions. Results from three models as well as simulation models are compared and analysis is conducted. The results show that the proposed approach allows decision makers to perform trade-off analysis among expected costs, quality acceptance levels, and on-time delivery distributions. It also provides alternative tools to evaluate and improve supplier selection decisions in an uncertain supply chain environment.     

Making real options work for practitioners: a generic model for valuing R&D projects

We propose a generic valuation framework for the appraisal of R&D projects based on real option theory. The added value of this approach is the presentation of a model that was implemented in a manner that allows corporate decision makers to use real options in an intuitive and standardized way. The project valuation procedure is separated into three main phases: project modeling, data and input collection, and result generation and analysis. The project model represents the structure of the real world R&D project with its investments, expected results, and decisions that need to be taken conditionally on the outcomes of research activities. The project model is represented in the form of a decision tree, where different research results or taken decisions lead to new branches. In this way, every possible situation the project can pass through can be represented. Uncertainties are separated into market uncertainties (e.g., market prices) and project specific, private uncertainties (e.g. uncertainty of research results). For both uncertainties, event trees are constructed which are then combined and merged with the above mentioned decision tree in order to represent the value evolution of the R&D project under given decisions and uncertainties. For every possible state of the project the real option value is calculated. By creating multidimensional trees, a multitude of decision steps and various kinds of real options (e.g., continue, expansion, switch, abandonment) can be modeled. The calculation complexity for the decision trees is given. From the tree structure we can calculate the real option value of starting an R&D project, i.e., the value of undertaking the first investment and thus acquiring the subsequent decision opportunities given by the completion of the first research effort. Furthermore, the optimal exercise strategy is derived from the decision tree. The exercise strategy gives the manager the possibility to have an a priori overview of where an R&D project may lead to, which decisions need to be taken in which circumstances, and when the project needs to be stopped in order not to generate losses. In an in‐depth case study we use an illustrative R&D project to set up and discuss the three phases of project modeling in the real options framework: building the multidimensional decision tree, input generation, and calculation of the real option value as well as the optimal strategy for the R&D project.     

Technical Note: Defining Project Scale

Most policy debates are fought largely with volleys of ideological slogans rather than evaluations of the costs and benefits arising from alternative proposals. The failure to measure costs and benefits creates a vacuum, rendering the political process more susceptible to manipulation by special interests. A lack of information regarding costs and benefits can also inhibit negotiations for mutually beneficial compromises. The failure to employ cost benefit analysis arises from the expense and time involved in measuring complicated phenomena. In addition, when decision makers do employ cost benefit analysis, they often omit significant gains and losses due to difficulties encountered in collecting information. In order to remedy these difficulties policy makers must make better use of computer software, which is currently being developed.     

Understanding the exploration–exploitation dilemma: An fMRI study of attention control and decision‐making performance

This paper studies the cognitive processes that enable decision makers to switch between exploitation and exploration. We use functional magnetic resonance imaging (fMRI) in a sample of expert decision makers to make two main contributions. First, we identify and contrast the specific brain regions and cognitive processes associated with exploitation and exploration decisions. Exploitation activates regions associated with reward seeking, which track and evaluate the value of current choices, while exploration relies on regions associated with attentional control, tracking the value of alternative choices. Second, we propose and test the idea that stronger activation of the brain circuits related to attentional control allows individuals to achieve better decision‐making performance as a result. We discuss the implications of these results for strategic management research and practice. Copyright © 2013 John Wiley & Sons, Ltd     

Contribution of productivity and firm size to value-added: Evidence from Vietnam

A new indexing method is developed to decompose the contributions of productivity, prices and firm size to a firm's value-added. The method introduces an error term into the decomposition equation to capture measurement biases which are caused by using the deflator instead of the observed price and all other sorts of measurement error. An application of the method is given using private small and medium manufacturing firm level data in Vietnam from 1996 and 2001. The error index decomposition method provides a comparison of performance of all firms to the hypothetical representative firm. The analysis allows firms and policy makers to realize the key factors contributing to the success or failure of a firm and suggest strategies to improve firm economic performance.     

Cost-effectiveness of patient-specific motion management strategy in lung cancer radiation therapy planning

Abstract

Cost-effectiveness analysis (CEA) in medicine is a form of economic study that compares the relative value of medical technologies and health care services. It helps decision makers to formally evaluate proposed interventions and make informed choices based on the estimated health gains per dollar spent under each intervention. This study employs a CEA framework to assess an emerging imaging technology to determine whether its adoption will be appropriate in routine patient care. A significant challenge in lung cancer radiotherapy (RT) is respiration-induced tumor motion during positron emission tomography/computed tomography (PET/CT). Respiratory gating may improve the image quality and delivery of curative doses to tumor. Respiratory-gated PET/CT is especially useful for locally advanced and inoperable non–small cell lung cancer (NSCLC). Due to the heterogeneity in patients’ respiratory patterns, questions remain regarding who will benefit from respiratory gating. The effectiveness of respiratory gating can be measured by using quantitative improvements in PET/CT images. We previously developed a patient-specific motion management (PSMM) paradigm to identify patients who benefited from respiratory-gated PET/CT based on respiratory pattern analysis. This article presents a new CEA framework to evaluate the cost-effectiveness of PSMM compared to the population-based radiation oncology practice of motion management in more than 1,500 cancer patients.     

Mental models,decision rules,and performance heterogeneity

This paper focuses on the role of managerial cognition as a source of heterogeneity in firm strategies and performance. We link differences in mental models to differences in decision rules and performance in a management simulation. Our results show more accurate mental models lead to better decision rules and higher performance. We also find that decision makers do not need accurate knowledge of the entire business environment; accurate mental models of the key principles are sufficient to achieve superior performance. A fundamental assumption in much of strategic management is that managers who have a richer understanding about organizational capabilities and the dynamics of industry structure can improve the performance of their firms. Our findings provide empirical evidence supporting this assumption and show that differences in mental models help explain ex ante why managers and firms adopt different strategies and achieve different levels of competitive success. Copyright © 2010 John Wiley & Sons, Ltd.     

A Model of the Asset Disposition Decision of the RTC

The purpose of this paper is to develop a model of the asset disposition decision for the Resolution Trust Corporation (RTC). In this paper, we focus on the primary goal of the RTC—to maximize the net present value of the cash flows generated through holding and selling the assets it acquires. A major decision it faces is whether to hold or sell assets. This decision ultimately depends on the RTC's discount rate versus that of the marginal buyer. A second question relates to the decision of which assets to sell first and which ones to delay sale. The model developed in this paper characterizes the asset disposition decision process of the RTC for different types of assets. We develop a set of optimal disposition rules based on the simple premise of a multi-period cash flow maximization. In addition, we test some of these rules by analyzing RTC disposition performance. Through this exercise, we hope to provide some guidance to the RTC in implementing its enormous task as well as to policy makers in charting the progress of the RTC. The main results of this analysis indicate that liquid assets and retail deposit franchises should be sold as quickly as possible. Illiquid assets that are performing and do not have high servicing costs are good candidates to finance through senior/subordinated securities or sale with seller financing by the RTC. Illiquid non-performing assets are good candidates for equity participation financing by the RTC. The sales proceeds obtained by the RTC will be increased if buyers have greater certainty with respect to expected cash flows and RTC sales policies.     

Managing strategic intellectual property assets in the fuzzy front end of new product development process

The strategic use of intellectual property (IP) is crucial for technology-based companies to gain competitive advantage. The recent transformation of the US patent system brings new challenges and opportunities in this arena. In this regard, this study attempts to identify techniques which can help with IP evaluation and selection in the fuzzy front end (FFE) of new product development (NPD) process. This study combines data collection methods such as mining the literature, conducting in-depth interviews, surveying questionnaires, and analyzing cases. This research serves as an analysis of modern literature and identifies a multicriteria weighted scoring model that can be employed to help with the patent decision process. The criterion to discern patent eligibility is a contended discussion. For this survey administration, 300 companies, as the targeted sample, were randomly selected to be reached from LexisNexis database. Consequently, this paper identifies the key decision criteria to incorporate into this model and obtains weights gathered from surveying IP professionals and R&D managers in US-based electronics manufacturing firms (SIC code: 36). This study proposes a structured approach to identify ideas that should be patented in the FFE of NPD process by way of an analysis of pertaining literature and case studies. The technique we present in this paper could be essential for many firms to achieve IP success as their strategic means. Moreover, this tool can help R&D managers not only speed up the FFE of NPD process but also make more informed and target-worthy decisions for IP filing.     

Trade and invasive species risk mitigation: Reconciling WTO compliance with maximising the gains from trade

This paper analyses the issue of balancing the gains from trade with the risk of pest and disease transference. Two decision frameworks for determining whether or not to permit trade in a potentially invasive species-carrying good are presented. The first considers only the potential production losses resulting from an invasive species entering through a trade pathway, as is prescribed by WTO compliance. The second is a unilateral welfare-maximising approach which considers the consumer gains from trade, the loss of domestic producers’ market share and expected damage from the invasive species. It is shown that these alternative decision frameworks can be reconciled such that they produce the same outcome regarding whether or not trade is to be permitted. The key parameters which influence these decisions are also highlighted.     

Assessing the economic costs of a foot and mouth disease outbreak on Brittany: A dynamic computable general equilibrium analysis

Outbreaks of animal diseases such as foot and mouth disease (FMD) are of great concern for agriculture. In this paper, we quantify the potential dynamic impacts of such a disease on Brittany, a French region with an important livestock sector. In order to do this, we develop a dynamic computable general equilibrium model that allows us to measure the impacts on the livestock sectors and downstream food industries. We study the impacts of a FMD outbreak including the culling infected animals, a temporary decline in demand, and restrictions on movements of live animals and meats during the FMD outbreak period.Our results show that economic losses following this disease are spread over many periods even with a one-time shock. We also find that the impacts on the various primary sectors and downstream food sectors are quite different, depending on their initial trade position. Our general equilibrium results show the great incidence of potential constraints affecting factor markets. Capital and wage constraints severely increase the aggregate costs of such disease. These results challenge the definition of a simple efficient management policy for this disease.     

Food scandals,media attention and habit persistence among desensitised meat consumers

Consumer reactions to food scandals and their resulting economic implication are well documented. However, studies have typically neglected the roles that consumption habits and media usage behaviours may play in explaining household’s response to food safety incidences. In this study we develop a model of heterogeneous media usage intensity, information impacts and decay over time to estimate household’s behavioural responses to the 2011 German Dioxin scandal. We are specifically interested in determining the degree of heterogeneity in household’s short-term adjustments demand patterns versus persisting long-term consumption habits of meat products (chicken and pork) directly affected by the incident. The empirical analysis employs detailed household-level retail scanner and media usage data collected by the GfK Consumer Scan panel for a total of 16,023 households over a period of 104 calendar weeks. Results of dynamic correlated random effect Tobit models indicate an important role of unobserved heterogeneity in explaining household responses during the food scandal. We find strong empirical evidence supporting our hypothesis that short-term marginal adjustments in demand and propensity to buy affected products triggered by the negative impact of household media exposure were over-compensated by habit persistence. The question of how consumption patterns evolve over time in the presence of food scandals is expected to be of interest for both policy makers and the food industry. The potential biases in the projection of economic impacts resulting from simplifying assumptions of household’s response patterns to a proliferating numbers of food safety incidences has implications for risk management and public policy.     

Design of sustainable supply chains under the emission trading scheme

Increase in environmental concerns together with legislations are forcing industries to take a fresh look at the impact of their supply chain operations on the environment. This paper introduces a mixed-integer linear programming based framework for sustainable supply chain design that considers life cycle assessment (LCA) principles in addition to the traditional material balance constraints at each node in the supply chain. Indeed, the framework distinguishes between solid and liquid wastes, as well as gaseous emissions due to various production processes and transportation systems. The framework is used to evaluate the tradeoffs between economic and environmental objectives under various cost and operating strategies in the aluminum industry. The results suggest that current legislation and Emission Trading Schemes (ETS) must be strengthened and harmonized at the global level in order to drive a meaningful environmental strategy. Moreover, the model demonstrates that efficient carbon management strategies will help decision makers to achieve sustainability objectives in a cost-effective manner.