具体描述
本书以企业集团为研究对象，针对企业集团管理过程中出现的一系列问题，采用数理经济学方法，特别是以博奕论为工具，向读者介绍包括企业集团的生产经营、形成动因、组织结构和最佳规模、内部的信息交流与激励机制设计、投资决策、公共费用分摊、技术创新战略以及技术合作等企业集团管理决策方面的内容。本书特别运用现代经济博奕理论研究了一系列前沿问题，在经济学、管理学与系统科学的集成上做了创新性的工作，在国内，同类型的著作尚未见到。
作者简介
目录信息
前言
绪论
第一章 数理经济学基础
第二章 企业集团的生产经营战略
第三章 企业集团的组织结构和规模
第四章 企业集团的协调与激励
第五章 企业集团投资与公共费用分摊
第六章 企业集团的技术创新策略
第七章 企业集团的技术合作
重要词汇英汉对照
符号说明
· · · · · · (收起)
读后感
评分
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用户评价
The very premise of “企业集团管理决策的数理分析” immediately caught my attention as someone fascinated by the intersection of logic and business strategy. Large conglomerates, by their very nature, operate with a scale and complexity that demands more than just intuition. The “数理分析” aspect signals a commitment to leveraging rigorous analytical methods to navigate this complexity. I’m particularly interested in how the book might address the application of control theory principles to manage dynamic business processes, such as optimizing production schedules in response to fluctuating demand or managing cash flow in a volatile economic environment. The concept of feedback loops and stability in complex systems is highly relevant to corporate governance. Furthermore, I’m curious about the potential exploration of game theory in strategic decision-making, particularly in competitive market scenarios. How can a firm anticipate and respond to the actions of its rivals using analytical models? This is a critical area for gaining and sustaining competitive advantage. The book might also touch upon methods for performance measurement and benchmarking, employing statistical techniques to compare operational efficiency across different divisions or against industry best practices. This is essential for driving continuous improvement. Ultimately, I see this book as a potential guide to building a more analytical culture within an enterprise, one where data is not just collected, but actively used to inform and optimize every facet of management. It's about equipping leaders with the quantitative tools to make smarter, more reliable decisions in a world that is increasingly driven by data.
评分作为一个对商业世界充满好奇的观察者，我总是被那些能够将复杂问题化繁为简，并给出清晰解决方案的理论所吸引。而“企业集团管理决策的数理分析”这个标题，正是我一直在寻找的那种能够将抽象的商业情境与具体的数学工具相结合的桥梁。在如今这个数据爆炸的时代，企业积累了海量的运营数据，然而，如何将这些原始数据转化为有价值的商业洞察，并最终指导决策，却是一个普遍存在的难题。这本书的出现，恰好填补了我在这方面的知识空白。我非常期待书中能够详细阐述如何运用统计学原理，例如假设检验、置信区间等，来验证企业经营中的各种假设，并对未来的发展趋势做出可靠的预测。同时，我也希望能够学习到如何在复杂的数据集中识别出潜在的模式和相关性，例如使用聚类分析来细分市场，或者使用关联规则挖掘来发现产品之间的销售联系。对于企业集团而言，协同效应和规模经济是其重要的优势，但如何量化这些优势，并将其转化为具体的管理策略，也需要精密的数理分析。我希望能在这本书中找到关于这些方面的理论和方法论。此外，在企业进行并购、重组或者投资决策时，如何进行有效的财务建模和风险评估，也是至关重要的。我期待书中能够提供一些关于估值模型、敏感性分析以及蒙特卡洛模拟等技术在企业决策中的应用实例。总而言之，我相信这本书将不仅仅是一本学术著作，更是一本能够赋能企业管理者，帮助他们提升决策能力，最终实现企业价值最大化的实用指南。
评分当我看到《企业集团管理决策的数理分析》这本书时，我 immediately felt a resonance. It spoke directly to a need I’ve increasingly felt in my own observations and studies of business: the need for a more rigorous, data-driven approach to decision-making, especially within the complex ecosystems of large corporations. The promise of “数理分析” (mathematical analysis) suggests a move beyond gut feelings and anecdotal evidence towards a more quantifiable and predictive framework. I’m particularly keen to explore how the book might delve into areas like econometrics and statistical inference to help businesses understand causal relationships between different operational variables and their ultimate impact on performance. For instance, how can a company reliably measure the ROI of its marketing campaigns, or the impact of employee training on productivity, using sound statistical methods? The title also hints at the application of operations research techniques, such as queuing theory to manage service bottlenecks or network optimization to streamline logistics. These are areas that, when applied correctly, can unlock significant efficiencies and cost savings. Furthermore, I anticipate discussions on scenario planning and simulation, utilizing mathematical models to explore the potential outcomes of different strategic choices under various market conditions. This would be invaluable for long-term strategic planning and risk mitigation. The ability to translate complex business challenges into solvable mathematical problems is a powerful skill, and I believe this book could be a crucial resource in developing that proficiency. It’s not just about crunching numbers; it’s about using numbers to build a more robust, resilient, and ultimately, more successful enterprise.
评分When I came across the title, “企业集团管理决策的数理分析,” I felt an immediate intellectual pull. The phrase “数理分析” suggests a departure from the often qualitative and experience-based approaches to management, moving towards a more precise and evidence-driven methodology. For large corporate structures, where decisions can have far-reaching implications, this rigorous approach is invaluable. I’m eager to learn about how the book might detail the use of simulation techniques, such as Monte Carlo simulations, to model the impact of various investment strategies or new product launches under different economic scenarios. This ability to “test drive” decisions before committing resources is a powerful advantage. The book could also shed light on the application of queuing theory in optimizing customer service operations or managing call center workloads, ensuring efficient resource allocation. In the realm of marketing, I anticipate discussions on advanced statistical modeling for customer segmentation and targeted advertising, potentially utilizing techniques like conjoint analysis to understand customer preferences. The optimization of marketing spend based on data-driven insights is crucial for maximizing ROI. Moreover, for a conglomerate, effective internal resource allocation is paramount. I hope the book explores mathematical programming techniques, such as linear or integer programming, to optimize the deployment of capital, personnel, and physical assets across various business units. This is about ensuring that the whole is truly greater than the sum of its parts, a feat that requires sophisticated quantitative planning. This book promises to offer a roadmap for transforming complex business challenges into analytically tractable problems, thereby enhancing the quality and reliability of corporate decision-making.
评分收到这本书的那一刻，我便被它那份沉甸甸的知识分量所吸引。封面上“企业集团管理决策的数理分析”这几个字，在我脑海中勾勒出一幅宏大的画面：一个庞大的企业集团，在纷繁复杂的市场环境中，如何运用数学的严谨性和逻辑性，去驾驭其庞大的体系，做出一个个关乎生死存亡的关键决策。这不仅仅是关于数字的游戏，更是关于如何在不确定性中寻找确定性，如何在海量信息中提炼核心价值，如何在竞争激烈的环境中保持领先地位的智慧。我一直对企业管理背后的逻辑规律感到着迷，而“数理分析”这个词，则将这种逻辑推向了一个全新的高度。我迫不及待地想要了解书中是否会深入探讨诸如线性规划、整数规划、非线性规划等优化方法，这些方法在资源分配、生产调度、物流配送等领域具有怎样的应用潜力。同时，我也会关注书中是否会介绍一些高级的统计建模技术，例如主成分分析、因子分析，它们如何帮助我们从多维度的企业数据中挖掘出关键的影响因素，从而更有效地理解企业运营的驱动力。此外，风险管理也是企业集团运营中不可或缺的一环，我希望书中能够提供关于风险量化、风险建模以及风险对冲的数理方法，帮助企业更科学地识别、评估和应对各种潜在风险。从企业战略的制定到具体运营的执行，每一个环节都离不开科学的决策支持。这本书的出现，无疑为我提供了一个深入学习和探索的绝佳机会。我期望它能为我打开一扇通往更理性、更科学的企业管理世界的大门，让我能够以更专业的视角去审视和分析企业面临的各种挑战，并提出更具建设性的解决方案。
评分From the moment I saw the title, “企业集团管理决策的数理分析,” I recognized its potential to be a groundbreaking resource. The phrase “数理分析” evokes a sense of rigor and scientific method applied to the often messy and intuitive world of business management, particularly within the vast scope of a corporate group. I’m excited to learn how the book might illuminate the use of operations research methodologies, such as network analysis for optimizing supply chain routes or facility location models to determine the most strategic placement of production plants or distribution centers. These are tangible problems with significant financial implications that require sophisticated quantitative solutions. The book could also explore the application of time series analysis for understanding and predicting economic cycles, market trends, or even the impact of seasonal variations on business performance. Such predictive capabilities are essential for proactive strategic planning. In the realm of human resources, I'm interested to see if the book covers quantitative approaches to workforce planning, talent management, and performance evaluation, perhaps utilizing statistical methods to identify key factors influencing employee engagement and productivity. Moreover, for a multinational corporation, managing currency exchange rate fluctuations and assessing international investment risks is crucial. I anticipate discussions on financial modeling, hedging strategies, and perhaps even the application of econometric models to understand global economic influences. This book seems poised to offer a powerful toolkit for transforming complex corporate challenges into analytically solvable problems, thereby enhancing the overall quality and strategic impact of management decisions.
评分这本书的封面设计就透着一股严谨和专业，金色的书名在深邃的背景下显得格外醒目，让我对它充满了好奇。我一直认为，现代企业经营管理，尤其是在竞争激烈的全球化市场中，已经无法仅凭经验和直觉来支撑。数据，才是最真实、最有说服力的语言。这本书的标题“企业集团管理决策的数理分析”正击中了我内心深处对科学化决策的渴望。我非常期待能够在这本书中找到将复杂的商业数据转化为清晰、可操作的管理洞见的工具和方法。在我过去的学习和实践中，常常会遇到大量的数据，但如何有效地提炼信息，识别趋势，预测未来，并最终做出最优的决策，这始终是一个巨大的挑战。很多时候，我们能够收集到海量的数据，但却缺乏将这些数据转化为智慧的有效途径。这本书承诺的“数理分析”正是解决这个问题的关键。我希望能深入了解书中介绍的各种数理模型和统计方法，例如如何运用回归分析来预测销售额，如何通过时间序列分析来评估市场波动，或者如何使用运筹学中的优化模型来配置资源。当然，我更关心的是这些抽象的数学工具如何在实际的企业管理场景中落地，如何帮助企业在战略规划、市场营销、生产运营、财务管理等各个环节做出更明智、更具前瞻性的决策。我希望这本书不仅仅是理论的堆砌，更能提供丰富的案例研究，展示这些数理分析方法是如何被成功的企业所应用，从而带来切实的业务增长和竞争优势。一个好的管理决策，往往能决定一个企业能否在风云变幻的市场中脱颖而出，而数理分析无疑是提升决策质量的重要手段。我期待这本书能够成为我手中的一把利器，帮助我更深入地理解企业运营的内在逻辑，更精准地把握市场机遇，更有效地规避潜在风险。
评分这本书的名字本身就透露出一种强大的力量感和深度，仿佛在诉说着如何用数学的语言来驾驭企业这座庞大的“航母”。我一直深信，真正的管理智慧，离不开对事物内在逻辑的深刻洞察，而数理分析恰恰是揭示这种逻辑的利器。在我看来，一个成功的企业集团，绝不是依靠偶然的机遇，而是依赖于一系列基于严谨分析和科学预测的决策。因此，我对于这本书中可能涉及到的各种分析工具和方法论充满了期待。我希望能了解书中是否会深入探讨如何利用决策树、博弈论等工具来分析竞争对手的行为，并制定出最优的竞争策略。同时，我也对如何运用时间序列分析来预测股票价格、商品价格甚至宏观经济指标，以及这些预测如何影响企业的投资和风险管理决策非常感兴趣。企业集团的运营涉及到资源的优化配置，例如生产线上的瓶颈分析、供应链的效率提升、以及人力资源的合理分配等，这些都是可以通过数理模型来解决的问题。我期望书中能提供具体的模型构建和求解方法，并附带真实的企业案例来加以说明。此外，在信息技术飞速发展的今天，大数据和人工智能正在深刻地改变着企业的运营模式。我希望书中能够探讨如何将这些新兴技术与数理分析相结合，例如如何利用机器学习算法来预测客户流失，或者如何通过深度学习模型来优化生产流程。这本书的出现，为我提供了一个绝佳的学习机会，让我能够以更加系统、更加专业的方式来理解企业管理中的各种复杂问题，并掌握解决这些问题的科学方法。
评分The title, “企业集团管理决策的数理分析,” resonated deeply with my ongoing interest in how organizations can systematically improve their decision-making processes. Large, complex entities like conglomerates face a multitude of interconnected challenges, and the “数理分析” component suggests a pathway to addressing this complexity with precision and logic. I’m particularly keen to explore how the book might explain the application of forecasting models, such as ARIMA or exponential smoothing, for predicting sales trends, demand fluctuations, or even financial performance metrics. Accurate forecasting is foundational for effective planning. Furthermore, the book might delve into the use of statistical process control (SPC) techniques to monitor and improve operational quality, ensuring consistency and reducing variability across different manufacturing or service processes. This focus on continuous improvement through data analysis is critical for long-term success. For a diversified business group, understanding the interplay between different business units and their impact on overall corporate performance is vital. I hope the book discusses techniques like correlation analysis or regression analysis to identify these interdependencies and inform strategic resource allocation decisions. The challenge of optimizing capital structure and managing financial risk also requires sophisticated quantitative tools. I anticipate discussions on valuation models, sensitivity analysis, and perhaps even the application of real options theory to strategic investment decisions. This book appears to be a comprehensive resource for anyone seeking to harness the power of mathematics to drive more informed, effective, and ultimately more successful business outcomes within a large organizational framework.
评分What immediately struck me about the title, “企业集团管理决策的数理分析,” was its direct relevance to the challenges faced by modern large-scale organizations. In an era defined by data abundance and intense competition, the ability to make informed, evidence-based decisions is no longer a luxury but a necessity. The “数理分析” component suggests a focus on the quantitative tools and frameworks that underpin effective management. I’m eager to see if the book explores the application of multivariate statistical techniques, such as discriminant analysis or logistic regression, to identify key drivers of customer loyalty or employee retention. Understanding these underlying patterns is crucial for developing targeted retention strategies. The complexities of global supply chains also present numerous optimization opportunities, and I hope to find discussions on techniques like inventory control models or facility location problems. How can a multinational corporation ensure its supply chain is both efficient and resilient in the face of disruptions? This requires sophisticated quantitative analysis. Moreover, in financial management, the book might cover areas like portfolio optimization, option pricing, or credit risk modeling, all of which rely heavily on mathematical principles. The ability to quantify financial risks and opportunities is paramount for sustainable growth. I believe this book could offer practical insights into how these analytical approaches can be integrated into the daily decision-making processes of a large enterprise, transforming raw data into actionable intelligence. It’s about moving from a reactive stance to a proactive, predictive one, driven by a deep understanding of the mathematical relationships that govern business outcomes.
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