管理实验--管理研究的重要方法

管理实验一直是管理研究的一种重要方法和工具,首先考察了管理学发展史上对实验方法的应用,比较研究了大量的管理实验,进而归纳出管理研究中实验方法的体系与分类,并详细分析了管理实验发展的四个阶段、主要特征以及在实际的管理研究中实验方法和手段的运用情况,最后对管理实验在我国的发展前景进行了分析.     

管理科学研究中的数学模型

管理科学是研究现实社会中人的管理活动的学问,其研究对象是社会和人,具有不确定性和主观性,因此在运用自然科学工具特别是数学工具时应格外注意,不能为数学而数学,应该在考虑研究对象特殊性的基础上,灵活运用数学工具.本文探讨了在管理科学研究中运用数学工具的过程中存在的问题,进而提出了应对的方法.     

基于计算实验的科技资源配置结构优化研究

从系统整体的角度构建了基于科技资源流动的国家创新体系运行概念模型,通过系统模拟与计算实验探讨了科技人力资源、科技财力资源和科技信息资源在高校、科研机构与企业之间不同分配方案下,我国论文与专利产出的可能变动情况,以期为政府相关部门制定科技资源优化配置政策提供参考。     

《计算实验金融研究》

金融系统本质上是由大量具有适应性、相互交互的个体组成的复杂系统。本次全球金融危机表明,金融市场规模不断增大和金融风险事件频发凸显出认识金融系统复杂演化规律、并提供相应风险管理手段的重要性。随着信息技术的迅猛发展,计算实验为获得这种科学认识提     

新创企业品牌联合伙伴选择的计算实验研究

品牌联合是新创企业克服其成长劣势的有效策略之一。为提高新创企业选择品牌联合伙伴的成功率,基于复杂适应系统理论构建了新创企业品牌联合企业主体行为活动的基本模型和主体之间、主体与环境之间的交互模型;研究了外部竞争环境、合伙企业的企业类型、品牌资产、关系承诺和联合匹配性等特征对联合形成的影响。结果表明：在外部环境动态变化时,越来越多的新创企业会选择品牌联合策略,而其选择成熟企业还是新创企业作为联合伙伴,并不受外部环境变化的影响。在品牌联合系统中,作为核心的新创企业选择合伙企业时,其自身特征并不影响其是否采取联合策略;不管核心企业自身特征如何,均优先选择成熟企业作为联合伙伴;同时,合伙企业的关系承诺对联合伙伴选择的影响最显著,品牌资产次之,而联合匹配性影响不显著。候选企业在回应核心企业的联合请求时,其接受/拒绝联合的决策主要取决于核心企业对其评价的结果,其次是核心企业的品牌资产。研究结果对新创企业的管理实践具有重要的参考价值。     

商务模式创新复杂性研究的计算实验方法

商务模式及其创新的复杂性特征决定了商务模式创新研究有必要采用计算实验的方法.分析商务模式创新研究的基本思路,提出应用计算实验的方法研究商务模式创新的方法论基础及其基本框架.分析和比较计算实验与计算机仿真(模拟)的区别与联系,提出应用粒子群优化算法、遗传算法等智能算法和复杂适应系统理论模拟商务模式的演化过程,进而对商务模式创新进行计算实验研究的基本方法.认为基于智能算法的计算实验为商务模式创新复杂性研究提供了有效的方法论、工具和平台,是商务模式创新复杂性研究的根本途径.     

我国管理科学研究的重点问题剖析

基于知识、信息和计算机网络技术的发展,在分析国内外管理科学研究热点领域及其热点问题的基础上,提出了我国管理科学研究的重点问题,给出了管理科学研究的应对策略.     

我国管理科学研究的回顾与发展展望

本文利用详实的数据信息资料,对我国管理科学研究的现状特征进行了归纳分析,在此基础上提出了新世纪管理活动的特点与管理科学研究的趋势。     

计算实验金融工程：大数据驱动的金融管理决策工具

在大数据时代,金融系统更清晰地呈现出由其微观单元之间的适应性交互形成的复杂系统内在本质。但传统金融理论受限于数学可解性,常利用理性经济人等假设简化金融系统的一些微观因素,致使理论模型难以捕捉诸多真实金融异象和风险事件,制约了理论的发展及其工程化应用。而今,金融系统的微观因素相关研究取得了重大突破,使得从微观主体异质行为及其交互出发的“自底向上”建模、以及相应的新型管理工具成为可能。这些研究推动了由大数据驱动的计算实验金融学、以及基于此的“计算实验金融工程”管理工具的发展。本文通过建立具有包容性的形式化概念模型,对传统金融和计算实验金融的逻辑和方法论进行阐述和比较,尝试在两者之间搭建对话桥梁。同时在上述模型框架下,通过示例展现了大数据驱动的计算实验金融如何拓宽金融科学理论的发展,并为金融实践中的管理决策带来新工具。     

基于计算实验的供应链联盟形成机制研究

采用计算实验方法模拟供应链联盟的形成过程,分析了供应链联盟成员主体行为的交互规则,重点研究了产品复杂性、核心企业能力因素对企业结盟策略选择的影响路径。结果表明,随着产品复杂程度的增加,核心企业结盟单个上游或下游企业的意愿增强,但当其复杂性超越一定临界值时核心企业更偏好于同时结盟上下游企业的策略,另外过高能力的核心企业结盟意愿低于能力不足的核心企业的结盟意愿。     

A bibliometric analysis of operations research and management science

Bibliometric analysis is the quantitative study of bibliographic material. It provides a general picture of a research field that can be classified by papers, authors and journals. This paper presents a bibliometric overview of research published in operations research and management science in recent decades. The main objective of this study is to identify some of the most relevant research in this field and some of the newest trends according to the information found in the Web of Science database. Several classifications are made, including an analysis of the most influential journals, the two hundred most cited papers of all time and the most productive and influential authors. The results obtained are in accordance with the common wisdom, although some variations are found.     

Determining causal relationships in leadership research using Machine Learning: The powerful synergy of experiments and data science

Machine Learning (ML) techniques offer exciting new avenues for leadership research. In this paper we discuss how ML techniques can be used to inform predictive and causal models of leadership effects and clarify why both types of model are important for leadership research. We propose combining ML and experimental designs to draw causal inferences by introducing a recently developed technique to isolate “heterogeneous treatment effects.” We provide a step-by-step guide on how to design studies that combine field experiments with the application of ML to establish causal relationships with maximal predictive power. Drawing on examples in the leadership literature, we illustrate how the suggested approach can be applied to examine the impact of, for example, leadership behavior on follower outcomes. We also discuss how ML can be used to advance leadership research from theoretical, methodological and practical perspectives and consider limitations.     

Top management support for management science

Two aspects of the relation between top managers and in-house management science units are considered in this paper. First, the impact of top management sponsorship and support on the progress and success of management science (MS) activities is considered. Secondly, the impact that an MS activity has had on the thinking and activities of top managers is discussed. The question of the role of the “professional” in an organization and the implications for client-professional perceptions of trust as these are influenced by the top manager are explored. Top management awareness and utilization of the management sciences are also reviewed.     

Business in Japan and the United States of America; some implications for management science and operations research

Significant differences exist between United States-managed and Japanese-managed organizations.

• •• U.S. firms are epitomized by surplus behaviors (emphasis on profits and returns on assets, investments and equity).
• •• Japanese firms are characterized by scarcity behaviors (emphasis on husbanding resources and reduction of waste).
• •• Management Science has been used in the generally surplus-oriented Western-world. Western values drive its application, or the decision not to apply it.
• •• Management Science can work effectively within a scarce-resource framework, as well as within a surplus-resource framework.
• •• Management Science has been barely used by the Japanese, although they might use it effectively. A possible explanation is that the Japanese culture is pervasive and consistent in dealing with scarcity.
• •• Management Science, when combined with a severe distaste for waste, may enable Western-world management to develop better strategies to achieve Global Competitiveness.
• •• The scarcity-oriented value system elevates the importance of people as resources. Management Science, to be effective, must do the same.

     

Cybernetics and the management science process

This paper addresses methodological issues currently confronting the management science community. The urgency of these issues is evidenced by [1] the growing debate over the implementability of MS/OR (Management Science/Operational Research) models, [2] the absence of professional agreement on a ‘generalized’ theory of organizational structure and control and [3] the dearth of substantive contributions in the area of ‘policy’ analysis and modeling. It is argued that any resolution of these issues must address the management science process and that developments in cybernetics provide an integrating framework for this purpose. Aspects of this framework are presented by pointing out distinctions between the more traditional MS/OR approaches and the proposed cybernetic approach. Some of the concepts involved are not always associated with cybernetics, but the implications for the practice of management science are significant.