基于因子分析与DEA方法的旅游上市公司效率评价

提出了基于因子分析的DEA组合评价方法。该方法综合了因子分析和DEA 2种方法的优点,以DEA为中心,以因子分析为辅助,通过因子分析法对投入产出指标进行处理,把繁多的投入产出指标归并成若干个具有明确经济意义的公共因子,从而利用DEA模型计算出各个决策单元的相对效率值,实现各决策单元的排序。通过我国旅游上市公司2000~2005年财务数据的评价说明这种方法的有效性。     

我国主要城市经济实力对比分析

本文从城市经济发展的四个方面选取了11个评价指标组成城市经济实力评价指标体系，采用因子分析对我国19个副省级及以上城市的经济实力进行综合分析，建立了城市经济实力的综合评价标准，对19个城市的经济实力得分进行排序并给出结果分析，将快速聚类法分类结果对因子分析结果进行验证说明     

我国股份制商业银行同国有商业银行竞争力比较分析

商业银行的竞争力是个综合复杂的体系,对不同的商业银行进行综合评价是比较困难的,必须建立一套适合的指标体系。文章运用多元统计分析SPSS12.0的主成分分析和因子分析方法对我国部分商业银行的竞争力进行综合评价分析,找出国有商业银行与股份制商业银行的差距,对国有商业银行的改革有一定借鉴意义。     

区间型符号数据的因子分析及其应用

符号数据分析是一种新兴的数据挖掘技术,区间数是最常用的一种符号数据。基于误差分析理论,研究针对区间数据的因子分析方法。将区间数看作一个由中点和半径构成的有序偶,并将半径视为区间数的极限误差。对中点样本阵进行因子分析,得到因子得分的中点值。然后将半径样本阵按照误差传递公式,得到因子得分的极限误差。由因子得分的中点值和极限误差最终得到因子得分的区间值。最后以股票的市场综合表现评价问题为案例,进行了应用研究。     

因子分析：上市公司综合业绩分析的一种新视角

上市公司的综合业绩是投资者据以进行投资判断的基本标准。随着企业投资价值被广大投资者所认可，投资者要求综合评估上市企业的绩效。因子分析法是一种有效的多元统计分析方法。借助因子分析方法，不仅可以考察上市公司的各项指标对上市公司业绩的影响程度，从中找出影响其业绩的主要因素。而且可以得到桌一类上市企业的综合排名，对投资者做出合理的投资决策具有很大的帮助。本文以山东省上市公司综合业绩的因子分析为例，建立了上市公司综合业绩分析的因子分析模型，并依据2003年的数据得出公司综合业绩排名的次序。     

基于因子分析的中国制造业行业自主创新能力评价研究

本文采用因子分析方法,对我国制造业29个行业的自主创新能力进行了定量评估及比较分析。抽取出来影响制造业自主创新能力创新活动与市场实现因子、学习因子和产出因子,并根据综合因子得分进行排序和分析评价,提出了一些有价值的政策建议。     

中国制造企业绿色供应链管理因素研究

随着经济全球化和中国入世,绿色供应链管理已逐步成为中国制造企业提升国际竞争力的重要战略。但是,绿色供应链管理在中国还处在起步阶段,缺乏相应的研究以指导实践。本文借鉴国外文献和国内环保专家设计问卷进行调研,采用因子分析方法,并借助社会科学统计软件SPSS,识别出中国制造企业绿色供应链管理压力/动力、实践和绩效的主要因子。在上述基础上,对数据结果进行分析,并结合中国制造企业的情况进行讨论。     

基于统计分析的中国制造业绿色供应链管理动力研究

随着资源紧缺和环境的恶化,绿色供应链管理作为循环经济在企业层面的实践,已成为制造业实现可持续发展的重要战略.借鉴国内外文献及环保专家的意见,设计问卷进行调研;借助社会科学统计软件SPSS,通过因子分析识别出中国制造业实施绿色供应链管理的压力/动力主因子;结合国内外相关情况探讨影响因子的作用机理,从而提出中国制造业绿色供应链管理的动力模型;最后提出企业开展绿色供应链管理实践的对策建议.     

天津市工业主要行业发展的比较研究

对天津市工业中十六个主要行业 1 997年的数据进行了主成分分析、聚类分析和因子分析 .提出用第一主成分作为行业规模的度量 ,第二主成分作为行业效益的度量 .进而从主成分分析和因子分析得出了各项经济指标反映行业经济效益、行业规模的情况和两个公共因子的含义 ,还从聚类分析中得出了各行业发展层次的分布情况     

新疆上市公司业绩评价的实证分析

本文运用多元统计方法中的因子分析方法.选取新疆上市公司12个财务指标建立因子模型.通过因子旋转提取出盈利因子、偿债因子、股本扩张因子和经营效率因子,并计算出各因子得分和因子综合得分,分别从盈利能力、偿债能力、股本扩张能力、经营效率及综合角度评价新疆上市公司业绩.     

经理层过度投资与股权激励的契约模型研究

为了获得控制权收益,经理层倾向于在有利于维持自身地位的项目上过度投资,从而形成了所谓“固守职位”的现象,这种行为损害了股东的利益。本文建立了一个简单的股东与经理层之间的契约模型,研究了股东如何设计最优契约来降低经理的过度投资问题,并考察了经理层过度投资程度与哪些因素有关。比较静态分析表明投资项目的风险状况通过所有者给予经理层的最优股权比例的变化间接影响过度投资程度;在存在经理人市场的条件下,外部替代的风险会使得这种保护自身职位的过度投资性行为更加突出。     

Anticipating acceptance of emerging technologies using twitter: the case of self-driving cars

In an early stage of developing emerging technologies, there is often great uncertainty regarding their future success. Companies can reduce this uncertainty by listening to the voice of customers as the customer eventually decides to accept an emerging technology or not. We show that risk and benefit perceptions are central determinants of acceptance of emerging technologies. We present an analysis of risk and benefit perception of self-driving cars from March 2015 until October 2016. In this period, we analyzed 1,963,905 tweets using supervised machine learning for text classification. Furthermore, we developed two new metrics, risk rate (RR) and benefit rate (BR), which allow analyzing risk and benefit perceptions on social media quantitatively. With our results, we provide impetus for further research on acceptance of self-driving cars and a methodological contribution to acceptance of emerging technologies research. Furthermore, we identify crucial issues in the public perception of self-driving cars and provide guidance for the management of emerging technologies to increase the likelihood of their acceptance.     

Production planning and inventory control in a company manufacturing PC parts: A case study

In this paper, we present a case study on the production planning and inventory system in a company manufacturing personal computer (PC) parts. In the case study, the targets are specified for developing a system for production planning and inventory control. The current state of the company is analysed for clarifying the points necessary to achieve the targets. Also, a system based on the analysis is proposed and its effects are estimated.     

供应链应收账款融资的决策分析与价值研究

根据供应链应收账款融资交易模型,建立了包含供应商、下游厂商和金融机构的多阶段供应链决策模型,研究了包含和不包含融资情况下相关企业的决策问题,得到供应链中各参与方在各阶段的期望收益,并通过数值分析研究了供应链应收账款融资对供应链成员和整个供应链的价值.分析发现:没有其他融资的情况下,中小供应商有可能出现生产不连续的情况,而供应链应收账款融资能够使其进行连续生产,并在快速增长的市场中能在较短的周期内达到最优产量;应收账款融资也能使厂商得到连续供货,收益持续增长,供应商的初始现金越多,厂商的期望收益越高;当供应商的实力较弱时,金融机构能够得到较大融资总收益,当供应商的实力达到一定程度后,金融机构得到的总收益呈下降趋势.供应链应收账款融资对中小供应商、厂商和金融机构都具有很大的应用价值.     

Intra-Organizational and inter-organizational resource allocation in two-stage network systems

There are organizational systems, such as bank branches and two-stage supply chains, which are composed of multiple parallel two-stage structures. Resource allocation in these systems is to maximize the benefit of the overall organization from a global viewpoint. In this study, we consider two types of systems at an organizational level: a centralized organizational system treating the whole two-stage production process as a basic unit, and a decentralized organizational system including two sub-organizations (groups) treating one of the two-stage production processes as a basic unit. We propose intra-organizational and inter-organizational resource allocation plans for two different organizational systems, respectively. Specially, two modes of free intermediate resource allocation (Free IRA) and fixed intermediate resource allocation (Fixed IRA) are discussed for the decentralized organizational system. The proposed allocation plans are based on two-stage data envelopment analysis models with bi-level formulations, in which the upper-level model is to maximize the entire organizational effectiveness (total outputs minus total inputs) by determining the optimized input resources and output targets while the lower-level model is concerned with efficiency constraints of all decision-making units simultaneously. The developed methods are illustrated by an application to a real-world problem with 17 city bank branches.     

Centralized resource allocation based on efficiency analysis for step-by-step improvement paths

The existing centralized resource allocation models often assume that all of the DMUs are efficient after resource allocation. For the DMU with a very low efficiency score, it means the dramatic reduction of the resources, which can cause the organizational resistance. In addition, in reality, it is particularly difficult for the DMUs to achieve their target efficiencies in a single step, especially when they are far from the efficient frontier. Thus, gradual progress towards benchmarking targets is gaining importance. In this paper, we present a new approach for resource allocation based on efficiency analysis under a centralized decision-making environment. Through our approach, the central decision-maker can obtain a sequence of intermediate benchmark targets based on efficiency analysis, which provide a level-wise improvement path to direct the DMUs to reach their ultimate targets on the efficient frontier in an implementable and realistic manner. Numerical examples are presented to illustrate the application procedure of the proposed approach.     

Illustration of a Method to Incorporate Preference Uncertainty in Benefit–Cost Analysis

Benefit–cost analysis is widely used to evaluate alternative courses of action that are designed to achieve policy objectives. Although many analyses take uncertainty into account, they typically only consider uncertainty about cost estimates and physical states of the world, whereas uncertainty about individual preferences, thus the benefit of policy intervention, is ignored. Here, we propose a strategy to integrate individual uncertainty about preferences into benefit–cost analysis using societal preference intervals, which are ranges of values over which it is unclear whether society as a whole should accept or reject an option. To illustrate the method, we use preferences for implementing a smart grid technology to sustain critical electricity demand during a 24‐hour regional power blackout on a hot summer weekend. Preferences were elicited from a convenience sample of residents in Allegheny County, Pennsylvania. This illustrative example shows that uncertainty in individual preferences, when aggregated to form societal preference intervals, can substantially change society's decision. We conclude with a discussion of where preference uncertainty comes from, how it might be reduced, and why incorporating unresolved preference uncertainty into benefit–cost analyses can be important.     

Assessing the Benefits and Costs of Homeland Security Research: A Risk-Informed Methodology with Applications for the U.S. Coast Guard

This article describes a methodology for risk-informed benefit–cost analyses of homeland security research products. The methodology is field-tested with 10 research products developed for the U.S. Coast Guard. Risk-informed benefit–cost analysis is a tool for risk management that integrates elements of risk analysis, decision analysis, and benefit–cost analysis. The cost analysis methodology includes a full-cost accounting of research projects, starting with initial fundamental research costs and extending to the costs of implementation of the research products and, where applicable, training, maintenance, and upgrade costs. The benefits analysis methodology is driven by changes in costs and risks leading to five alternative models: cost savings at the same level of security, increased security at the same cost, signal detection improvements, risk reduction by deterrence, and value of information. The U.S. Coast Guard staff selected 10 research projects to test and generalize the methodology. Examples include tools to improve the detection of explosives, reduce the costs of harbor patrols, and provide better predictions of hurricane wind speeds and floods. Benefits models and estimates varied by research project and many input parameters of the benefit estimates were highly uncertain, so risk analysis for sensitivity testing and simulation was important. Aggregating across the 10 research products, we found an overall median net present value of about $385 million, with a range from $54 million (5th percentile) to $877 million (95th percentile). Lessons learned are provided for future applications.     

Can a Previous Alliance Between an Acquirer and a Target Affect Acquisition Performance?

Throughout the 1990s, organizations have been combining resources through acquisitions and alliances in record numbers. An acquirer’s previous alliance with a target may give an acquirer target-specific information and experience that may be an advantage-producing resource in selection, valuation and integration of the target. This study investigates whether a previous alliance between an acquirer and a target affects post-acquisition performance and finds that a previous alliance between an acquirer and a target correlates positively with acquisition performance. Acquirers’ previous R&D, technology transfer, manufacturing and marketing alliances with targets benefit acquisition performance more than their previous licensing alliances with targets. Furthermore, target-specific learning effects are strongest and most beneficial to acquisition performance in acquirers’ previous technology transfer and manufacturing alliances with targets.     

Externalities in the wildland–urban interface: Private decisions,collective action,and results from wildfire simulation models for California

Property damage from wildfires occurs from spread into built-up areas, the wildland–urban interface. Fire spread occurs as embers from one burning structure ignite neighboring ones—but mitigation reduces the chances that fire spreads. In this study, we use a simulation model with realistic parameters for a neighborhood in California to illustrate patterns of marginal benefit from mitigation. We extend existing models of fire spread in two novel ways. We show how to describe the no-regulation equilibrium and social optimal levels of mitigation by incorporating data on a key factor, the distribution of house values in the community. We incorporate insurance in the model and show that it improves homeowner decision-making and insurance premium regulation. The fire spread simulations show that under plausible parameter values, there is a pattern in which mitigation's marginal benefit is low at low levels of community mitigation, rises to a maximum, and then falls quickly to a low level. We argue that the maximum marginal benefit is a guide to achieving optimal mitigation in a community. Owner mitigation decisions will depend on the distribution of house values in the neighborhood and other factors. In an illustration, we use the distribution of house values in a California community to illustrate the mitigation owners will choose under independent (Nash) investment decisions, and the efficiency-improving actions involving regulations or insurance premium subsidies that can lead to the social optimum.