论投资组合与金融优化 ———对理论研究和实践的分析与反思

经过50 多年的发展,投资组合选择的理论研究和实践已经取得了相当丰富的成果. 随 着全球经济一体化进程的加快和我国金融市场的发展与完善,我国金融机构对投资组合理论 的应用实践提出了具体要求. 按照投资组合选择理论的发展脉络,简述并分析了现代投资组合 选择的各种主要理论、模型与方法以及它们之间的内在关系,并对一些最新进展作了重点介 绍. 在此基础上,对投资组合选择(或广义意义下的金融优化) 的理论研究和在我国的应用实践 问题,提出了若干值得关注的发展方向与建议.     

论投资组合与金融优化 ———对理论研究和实践的分析与反思

经过50多年的发展,投资组合选择的理论研究和实践已经取得了相当丰富的成果.随着全球经济一体化进程的加快和我国金融市场的发展与完善,我国金融机构对投资组合理论的应用实践提出了具体要求.按照投资组合选择理论的发展脉络,简述并分析了现代投资组合选择的各种主要理论、模型与方法以及它们之间的内在关系,并对一些最新进展作了重点介绍.在此基础上,对投资组合选择(或广义意义下的金融优化)的理论研究和在我国的应用实践问题,提出了若干值得关注的发展方向与建议.     

Understanding the effects of outsourcing: unpacking the total factor productivity variable

Research on why firms should outsource and how they should do it has proliferated in the past two decades, but few consistent findings have emerged concerning the benefits of outsourcing. We argue that this is in part due to the lack of an adequate framework for measuring the effects of outsourcing. To address this, we present such a framework based upon the Cobb–Douglas productivity function. We explain how our framework can be used to unpack one component of the Cobb–Douglas productivity function, the ‘total factor productivity’, which represents the other numerous sub-variables that affect outsourcing productivity, beyond the capital and labour expenditures. We also demonstrate the framework using a simple illustrative example.     

A methodology for industrial studies of productivity performance

This article describes a methodology for measuring productivity and competitiveness in industry. The methodology is developed mainly for the mechanical industry (including shipyards, offshore and electromechanical companies). Two different approaches are described—one is based on a self-audit using a questionnaire answered by the industry itself, the second, using a more complete audit, is based on expert teams analysing the company. The productivity is described by indicators given points on a scale from 1 to 7 (1—far behind international competitors, 7—(best practice’).     

Managing seasonal fluctuations in demand. Practice and experience of selected industrial enterprises

Principles and methods of production management only seldom address the issue of seasonal variation. Yet, many industrial enterprises are confronted with heavy fluctuations over the year. This article reports on an industrial study of methods developed and applied in six Danish industrial enterprises. The methods represent different approaches to the management of seasonal variation and they often challenge traditions and call for a mental shift on the part of both management and workers.     

Technology-based total factor productivity and benchmarking: New proposals and an application

The present study fills a gap between the benchmarking literature and multi-output based efficiency and productivity studies by proposing a benchmarking framework to analyze total factor productivity (TFP). Different specifications of the Hicks–Moorsteen TFP index are tailored for specific benchmarking perspectives: (1) static, (2) fixed base and unit, and (3) dynamic TFP change. These approaches assume fixed units and/or base technologies as benchmarks. In contrast to most technology-based productivity indices, the standard Hicks–Moorsteen index always leads to feasible results. Through these specifications, managers can assess different facets of the firm's strategic choices in comparison with firm-specific relevant benchmarks and thus have a broad background for decision making. An empirical application for the Spanish banking industry between 1998 and 2006 illustrates the managerial implications of the proposed framework.     

Dynamic-objective particle swarm optimization for constrained optimization problems

This paper firstly presents a novel constraint-handling technique, called dynamic-objective method (DOM), based on the search mechanism of the particles of particle swarm optimization (PSO). DOM converts the constrained optimization problem into a bi-objective optimization problem, and then enables each particle to dynamically adjust its objectives according to its current position in the search space. Neither Pareto ranking nor user-defined parameters are involved in DOM. Secondly, a new PSO-based algorithm—restricted velocity PSO (RVPSO)—is proposed to specialize in solving constrained optimization problems. The performances of DOM and RVPSO are evaluated on 13 well-known benchmark functions, and comparisons with some other PSO algorithms are carried out. Experimental results show that DOM is remarkably efficient and effective, and RVPSO enhanced with DOM exhibits greater performance. In addition, besides the commonly used measures, we use histogram of the test results to evaluate the performance of the algorithms.This research is supported by National Natural Science Foundation of China (No. 10371028) and Scientific Research Fund of Southern Yangtze University (No. 0003182).     

An investigation of career development programs,job satisfaction,professional development and productivity: the case of Taiwan

This study attempts to develop career development programs capable of responding to career needs at different career stages. The current implementation status of these career development programs in Taiwanese businesses is then examined, along with the level of satisfaction of R&D personnel with available career development programs. The relationship between the career development programs and job satisfaction, professional development and productivity is then examined, revealing an association between high satisfaction of R&D personnel with career development programs and high job satisfaction, professional development and productivity.     

企业战略三维坐标体系及其风险测度

近年来,简化定量化测量企业管理实践的方法,一直是发达国家研究人员关注的重要课题。以往的定量化测量方法,基于二维测量,而且较复杂,即不变于企业测量,也不能全面描述企业管理实践的现状。文章作者基于长期大型企业集团高级经理人的实践,结合以往学者的研究成果,提出战略理论模型及战略融合度等新概念。文章提出的三维测量方法便于企业自我测量,并能较全面地描述企业管理实践现状及其风险。文章依据战略模型描述的案例,是某大型企业管理实践及其成长的真实案例。文章提出的战略模型及其测量方法,实现了企业管理实践测量方法的创新,丰富了该领域的研究。     

Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection

Multi-objective combinatorial optimization (MOCO) problems, apart from being notoriously difficult and complex to solve in reasonable computational time, they also exhibit high levels of instability in their results in case of uncertainty, which often deviate far from optimality. In this work we propose an integrated methodology to measure and analyze the robustness of MOCO problems, and more specifically multi-objective integer programming ones, given the imperfect knowledge of their parameters. We propose measures to assess the robustness of each specific Pareto optimal solution (POS), as well as the robustness of the entire Pareto set (PS) as a whole. The approach builds upon a synergy of Monte Carlo simulation and multi-objective optimization, using the augmented ε-constraint method to generate the exact PS for the MOCO problems under examination. The usability of the proposed framework is justified through the identification of the most robust areas of the Pareto front, and the characterization of every POS with a robustness index. This index indicates a degree of certainty that a specific POS sustains its efficiency. The proposed methodology communicates in an illustrative way the robustness information to managers/decision makers and provides them with an additional supplement/tool to guide and support their final decision. Numerical examples focusing on a multi-objective knapsack problem and an application to academic capital budgeting problem for project selection, are provided to verify the efficacy and added value of the methodology.     

成员企业权力结构对联盟中控制权不对称分布影响的研究

以我国电器制造企业间联盟为样本,考察了成员企业权力结构对联盟控制权不对称分布的影响.结果表明,成员企业的权力结构各因素显著影响着联盟控制权的不对称分布:内部联合权力水平会弱化这种不对称,而其冲突水平则会强化这一不对称;外部联合权力水平会显著强化这种不对称,内外部联合权力间的冲突水平也会强化这种不对称.同时,成员企业的权力结构相似性与联盟中控制权分布的不对称之间存在负相关关系,但这种关系并非线性关系,仅在成员权力结构具有高度相似性时,才会倾向于降低联盟控制权分布的不对称.     

Measurement and decomposition of the Malmquist productivity index for parallel production systems

The conventional Malmquist productivity index (MPI), which ignores the internal structure of a production system when measuring changes in performance between two periods, may produce misleading results. This paper thus takes the operations of the component processes into account in investigating the MPI of parallel production systems. A relational data envelopment analysis (DEA) model is developed to measure the biennial MPIs of the system and internal processes at the same time, and it is shown that the former is a linear combination of the latter. This decomposition helps identify the processes that cause the decline in performance of the system. An example of 39 branches of a commercial bank, with deposits, sales, and services as the three major functions operating in parallel, is used to illustrate this approach.     

An environmental life cycle optimization model for the European pulp and paper industry

Will paper recycling reduce the environmental impact of the European pulp and paper sector? If so, is maximal paper recycling the best policy to optimize the life cycle of the pulp and paper sector? We explore these questions using an approach that combines materials accounting methods and optimization techniques. Environmental impact data are inputs for a linear programming network flow model to find optimal configurations for the sector. These configurations consist of a mix of different pulping technologies, a geographical distribution of pulp and paper production, and a level of recycling consistent with the lowest environmental impacts. We use the model to analyse scenarios with different recycling strategies. Recycling offers a reduction in environmental impact in regions with a high population and a large production of paper and board products. Regions with a large production of graphic products should focus on cleaner virgin pulp production with energy recovery. We conclude that relocation of paper production also offers a reduction in environmental impact. However, the severe effects on the economy make this policy less attractive than a combination of recycling, cleaner pulp production and energy recovery.     

An empirical assessment of the operational performance through internal benchmarking: a case of a global logistics firm

This article solves an operational performance measurement problem of a global logistics firm through an internal benchmarking tool. The intended impact is to enable logistics firms to form a deeper understanding of their own internal processes and metrics. The methodology of this in-depth action research involves a sequential approach with a series of interviews, questionnaire-based surveys, operations data collated through observations and process mapping yielding real-world data. A series of statistical tests are conducted to analyse the collated data. Strategic priorities of the firm are integrated with the firm’s operational performance to ascertain the effective performance by considering both the tangible and intangible measures. The outcomes inform both practitioners and academics how the firm could improve its freight forwarding business’s profitability by ensuring that its operations meet the prioritised criteria. The ‘best practice’ derived from internal benchmarking forms an intermediate step towards external benchmarking. The outcomes facilitate investigating the current business strategy, the standard operating procedures and the scope of improving those.     

An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations

This paper addresses the resource-constrained project scheduling problem with uncertain activity durations. An adaptive robust optimization model is proposed to derive the resource allocation decisions that minimize the worst-case makespan, under general polyhedral uncertainty sets. The properties of the model are analyzed, assuming that the activity durations are subject to interval uncertainty where the level of robustness is controlled by a protection factor related to the risk aversion of the decision maker. A general decomposition approach is proposed to solve the robust counterpart of the resource-constrained project scheduling problem, further tailored to address the uncertainty set with the protection factor. An extensive computational study is presented on benchmark instances adapted from the PSPLIB.     

Linking inventory efficiency,productivity and responsiveness to retail firm outperformance: empirical insights from US retailing segments

This paper establishes an empirical model linking a retail firm’s inventory management effectiveness to superior competitive operational performance for specific product-line retail segments. Using 16?years of US retail firm financial data from the COMPUSTAT Fundamentals database across 12 distinct competitive retailing segments, we develop and test a time-series model that links several inventory management execution measures to the competitive operational outperformance of retail firms. The analysis presented provides strong evidence that measures of inventory management performance are not ‘one size fits all’ for the retail industry, and helps to explain why extant research has had difficulty linking inventory control policy effectiveness to operational performance advantages in retailing. We discuss the implications of these empirical findings on the study of inventory policy execution, and offer some guidance for further research.     

社会资本、吸收能力对创新绩效影响的实证研究

以企业知识理论为基础,从吸收能力这一视角出发,剖析企业外部社会资本和内部社会资本与企业创新绩效之间的关系;依据经典文献,对外部社会互动、基于认知的信任、共同语言、内部社会互动、基于情感的信任和共同愿景与知识识别、知识获取、知识共享和知识应用的关系进行重新梳理,并对知识应用与企业创新绩效的关系进行阐述;构建概念模型,并采用469个样本进行实证。研究结果表明,基于认知的信任、共同语言促进知识识别,外部社会互动、共同语言促进知识获取,内部社会互动抑制知识共享,基于情感的信任、共同愿景促进知识共享,基于情感的信任促进知识应用,知识识别促进知识获取,知识获取促进知识共享和知识应用,知识共享促进知识应用,知识应用促进企业创新绩效。从整体上看,吸收能力在企业社会资本对企业创新绩效的影响中起中介作用。     

内外控人格特质的研究及其在管理中的应用

内外控人格特质是个体对其行为及行为所产生的后果强化后的信念。内外控人格特质的不同不但影响个体对工作的态度,还影响着个体对组织的承诺感及满意度,从而影响到员工工作绩效和离职意图。通过对影响内外控人格特质的因素进行归纳,对目前常用的测量内外控人格特质的量表进行分类,并对内外控人格特质在管理中的应用进行分析的基础上,对国内外内外控人格特质的研究现状进行了较全面的概述,并在此基础上提出了5个方面的研究方向。     

Supply chain configuration for diffusion of new products: An integrated optimization approach

We develop an integrated/hybrid optimization model for configuring new products’ supply chains while explicitly considering the impact of demand dynamics during new products’ diffusion. The hybrid model simultaneously determines optimal production/sales plan and supply chain configuration. The production and sales plan provides decisions on the optimal timing to launch a new product, as well as the production and sales quantity in each planning period. The supply chain configuration provides optimal selection of options and safety stock level kept at each supply chain function. Extensive computational experiments on randomly generated testbed problems indicate that the hybrid modeling and solution approach significantly outperforms non-hybrid alternative modeling and solution approaches under various diffusion and supply chain topologies. We provide insights on optimal production/sales plan and supply chain configuration for new products during their diffusion process. Also, managerial implications relevant to effectiveness of the hybrid approach are discussed.     

An Enhanced Concave Program Relaxation for Choice Network Revenue Management

The network choice revenue management problem models customers as choosing from an offer set, and the firm decides the best subset to offer at any given moment to maximize expected revenue. The resulting dynamic program for the firm is intractable and approximated by a deterministic linear program called the CDLP which has an exponential number of columns. However, under the choice‐set paradigm when the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has been proposed but finding an entering column has been shown to be NP‐hard. In this study, starting with a concave program formulation called SDCP that is based on segment‐level consideration sets, we add a class of constraints called product constraints (σPC), that project onto subsets of intersections. In addition, we propose a natural direct tightening of the SDCP called , and compare the performance of both methods on the benchmark data sets in the literature. In our computational testing on the data sets, 2PC achieves the CDLP value at a fraction of the CPU time taken by column generation. For a large network our 2PC procedure runs under 70 seconds to come within 0.02% of the CDLP value, while column generation takes around 1 hour; for an even larger network with 68 legs, column generation does not converge even in 10 hours for most of the scenarios while 2PC runs under 9 minutes. Thus we believe our approach is very promising for quickly approximating CDLP when segment consideration sets overlap and the consideration sets themselves are relatively small.