具体描述
现代企业战略管理与组织行为学导论 第一部分：全球化背景下的企业战略制定与实施 第一章：战略管理基础与演进 本章深入探讨了战略管理的核心概念、历史演变及其在当代商业环境中的关键作用。我们将从经典的竞争优势理论（如波特的五力模型、价值链分析）出发，逐步过渡到资源基础观（RBV）和动态能力理论（DC）。重点分析了信息技术、全球供应链重塑以及社会责任要求如何深刻地改变了传统战略制定的范式。内容涵盖了战略愿景、使命、价值观的构建，以及如何将高层意图转化为可执行的战略目标（Objectives and Key Results, OKRs）。此外，本章详细阐述了战略实施过程中常见的组织惰性与变革管理挑战，并提供了结构化解决方案，以确保战略不流于口号，而是切实驱动业务成果。 第二章：市场环境分析与行业结构洞察 本章聚焦于外部环境的系统性扫描与深度解析。我们将运用宏观环境分析工具（PESTEL分析）来识别影响行业的政治、经济、社会、技术、环境及法律因素。在行业层面，除了经典的五力模型，本章引入了更具前瞻性的“竞争格局重塑”框架，探讨颠覆性技术（如人工智能、生物科技）如何从根本上改变现有行业的价值捕获机制。特别设立章节讨论新兴市场环境的独特性——包括制度缺失、信息不对称及快速增长带来的管理难题。通过大量案例分析，读者将学习如何从复杂数据中提炼出关键战略信号，并据此调整企业的进入、退出或防御策略。 第三章：竞争战略选择与定位 本章致力于阐述企业如何构建和维持可持续的竞争优势。内容涵盖了成本领先战略、差异化战略以及集中化战略的精细化操作。不同于理论概述，本章强调“价值捕获”与“价值创造”的平衡。对于成本领先，我们探讨了精益生产、供应链优化和数字化转型在降低运营成本中的实际应用；对于差异化，则深入分析了品牌资产构建、客户体验设计（CX）以及知识产权保护的战略价值。本章还讨论了“蓝海战略”在开辟新市场空间中的应用逻辑，并警示了“被卡在中间”的风险及规避方法。 第四章：企业成长战略与组合管理 本章系统性地梳理了企业实现增长的多种路径。首先分析了有机构建（有机增长）的内部驱动力，如产品创新周期管理、市场渗透与开发策略。其次，重点剖析了外部成长策略——并购（M&A）、合资（JV）和战略联盟。并购部分详细介绍了交易前尽职调查（Due Diligence）的财务、运营和文化维度，以及并购后的整合（PMI）挑战与最佳实践。对于多元化企业，本章运用业务组合管理工具（如GE矩阵）来评估不同业务单元的资源配置优先级，确保集团层面的协同效应最大化。 --- 第二部分：组织行为学与人力资源战略 第五章：组织结构设计与变革管理 本章探讨了高效组织结构的构建原则，解析了职能型、事业部型、矩阵型以及扁平化（敏捷）组织结构的优缺点及其适用场景。重点分析了在数字化转型和跨职能协作日益重要的今天，如何设计能够促进信息流动和快速决策的组织架构。此外，本章深入讲解了组织变革管理的科学流程，包括柯特（Kotter）的八步法和明茨伯格（Mintzberg）的组织干预模型，强调了高层承诺、员工参与和有效沟通在成功变革中的决定性作用。 第六章：领导力理论与高绩效团队建设 本章全面梳理了领导力的主要理论流派，从特质论、行为论到情境领导理论（SLT）和变革型领导（Transformational Leadership）。重点分析了当代情境下对领导者提出的新要求，例如在远程工作和全球分布式团队中，如何运用教练式领导和仆人式领导来激发员工潜能。在团队建设方面，本章聚焦于高绩效团队的特质（如心理安全感、明确的角色界定），并提供了促进冲突解决、增强团队凝聚力的实用工具和方法论。 第七章：企业文化塑造与价值驱动 本章将企业文化视为组织战略的“操作系统”。本章区分了组织表层文化（仪式、符号）与深层文化（基本假设、价值观），并引用沙因（Schein）的文化模型进行剖析。内容详细说明了高管行为、人力资源政策（招聘、激励、绩效管理）以及组织叙事在塑造和维护一致性文化中的关键作用。本章还专门讨论了在全球化运营中处理多元文化冲突（Culture Clash）的策略，以及如何建立倡导创新、风险承担和学习的文化。 第八章：员工激励、绩效管理与人才保留 本章构建了一个现代人力资源管理与战略目标挂钩的框架。激励理论（如期望理论、公平理论）的应用被置于绩效管理体系中讨论。重点分析了如何设计公平、透明且能够驱动预期行为的绩效评估系统，特别是如何将360度反馈、目标校准会议（Calibration Meetings）有效融入绩效循环。对于人才保留，本章超越了简单的薪酬福利讨论，深入探讨了职业发展路径规划（Career Pathing）、继任者计划（Succession Planning）以及基于优势（Strength-Based）的员工发展策略，旨在构建员工与组织共同成长的生态系统。 第九章：跨文化管理与全球人力资源挑战 在全球化深入的背景下，本章专门探讨了管理跨国工作团队所面临的独特挑战。内容包括霍夫斯泰德（Hofstede）的文化维度分析在跨文化沟通中的应用、外派人员管理（Expatriate Management）的策略选择（派驻、本土化、混合模式）及其风险控制。本章还分析了不同国家在劳动法、工会关系和薪酬福利体系上的差异，为读者提供在复杂全球环境中制定统一而又灵活的全球人力资源政策的指导。 --- 第三部分：运营效率与数字化转型 第十章：运营管理与供应链韧性 本章聚焦于如何通过高效的运营流程来支撑企业战略。内容覆盖了从需求预测、库存管理到生产计划的全面运营决策。特别强调了在当前地缘政治不确定性增加的背景下，如何构建具有韧性（Resilience）的供应链。我们将讨论供应链风险映射、多源采购策略以及数字化技术（如物联网、区块链）在提升供应链可见性和可追溯性方面的应用，以实现从“效率优先”到“效率与韧性并重”的转变。 第十一章：创新管理与技术商业化 本章系统阐述了企业创新从概念到市场化的全过程管理。内容涵盖了开放式创新（Open Innovation）的模式，包括与初创企业、大学及研究机构的合作机制。我们详细分析了研发投资组合管理（R&D Portfolio Management）的原则，确保资源投入与企业的长期战略方向一致。此外，本章提供了评估创新项目商业可行性的工具，如技术成熟度等级（TRL）与市场接受度分析，并指导企业如何构建支持快速原型设计和迭代的学习型组织。 第十二章：数字化转型与商业模式重构 本章将数字化视为驱动企业战略和运营变革的核心力量。内容不仅限于工具应用，更侧重于思维模式的转变。我们将分析云计算、大数据、人工智能等技术如何渗透到企业的价值链中，并催生新的商业模式（如平台经济、服务化转型）。本章指导读者如何识别和应对数字化转型中的组织壁垒、数据治理挑战，并构建一个持续适应技术进步的组织能力。 --- 本书旨在为企业管理者和有志于进入管理领域的专业人士提供一个既有坚实理论基础，又紧密贴合当代商业实践的全面指南。通过对战略、组织、人才与运营的整合性分析，读者将能够更有效地理解和驾驭复杂的商业环境，制定并成功实施驱动长期价值增长的综合性管理方案。
作者简介
目录信息
C 0 N T E N T S
Chapter l Proactive
Decision Making
Routine Decisions
The Challenges of Proactive
Decision Making
Alternatives
Assumptions-Structure
Assumptions-Assessments
Performance
Summary
Chapter 2 Alternatives
Small Number of Alternatives
Sequential Decisions
A Single Decision Quantity
Two or More Decision Quantities
Decision Rules
Summary
Chapter 3 Structuring Assumptions
in Decision Making
Structuring Relationships llsing an
Influence Diagram
Structuring a Sequence of Decisions
and Uncertainties Using a
Decision Tree
Influence Diagrams with
Uncertain Quantities
Final Examples of How to Develop an
Influence Diagram
The Use oflnfluence Diagrams and
Decision Trees
Case: Destiny Consulting Group
Chapter 4 Assessment
Sensitivity Analysis
The Language of Probability
Uncertainties with a Pew
Potential Outcomes
Uncertainties with Many
Potential Outcomes
Summary Measures of
Probability Distributions
Deriving the Probability Distribution
for Performance
Summary
Chapter 5 Performance
Relevant Monetary Flows
Evaluating Alternatives
under Uncertainty
Few Potential Outcomes
Many Potential Outcomes
Summary
Chapter 6 Risk Management
Value of Information
Perfect Information
Imperfect Information
Value of Control
Perfect Control
Control ofContinuously
Ranging Quantities
Adding Value and Reducing Risk
Summary
Chapter 7 Evaluating
Multiperiod Performance
Cash Flow
An Example
Time Value of Money '
Accumulated Value
Present Value and Net Present Value
Formulas for Accumulated and Present
Value Calculations
Streams in Perpetuity
Pretax versus Aftertax Analyses
The Reinvestment Rate
Hurdle Rate
Internal Rate ot Return
Nominal versus Effective Rates
of Return
Chapter 8 Multiobjective and
Multistakeholder Choice
The Generic Choice Problem
Example
First-Rbund Eliminations
Dominance
Decision Rules without Trade-
offJudgments
The Lexicographic Rule
Satisficing
Rate and Weight: Lin"'"' Additive
Scoring Rules
Rating Alternatives
Weighting Attributes
Assumptions ofRate and Weight
Multiple Stakeholder Problems
Appendix l Comments on the
Dependence ofWeights on the
Scaling of Attributes
Exercises
Chapter 9 Risk Preference
and Utility
The Utility of
Monetary Consequences
Risk Aversion
Constant Risk Aversion: Negative
Exponential Utility
Decreasing Risk Aversion:
Logarithmic Utility
Using a Utility Curve for Risk
Analysis
Separation of Risk-Return and Mean-
Variance Analysis
Corporate Risk Policy
Exercises
Chapter lO Competitor Analysis
Characterizing Competitive
Situations
Matrix Format
Classical Structures
No (or Little) Conflict
Prisoner's Dilemma
Preemption
Summary
Chapter ll Probability
Distributions
The Language ofProbability
Distributions
The Probability Mass Function
The Cumulative Distribution
Function - .,
Continuous and Many-Valued
Uncertain Quantities
Assessment: Capturing Personal
Judgment
An Example of Assessing a
Probability Distribution
Assessment: Using Historical Data as
a Guide
Identifying Suitable Data
Using the Suitable Data as a Guide
Adjusting Data for One
Distinguishing Factor
Assessment: Appealing to Underlying
Structure
The Binomial Distribution
The Normal Distribution
The Poisson Distribution
The Exponential Distribution
Subjective Biases and Assessment
Summary
Chapter 12 Sampling
Forecasting Sample Results
Forecasting a Sample Average
Forecasting a Sample Proportion
Using Sample Results to Draw
Inferences about the Underlying
Probability Distribution
Inferences about the Mean of
the Underlying Probability
Distribution
Inferences about the
Underlying Probability
Using Sample Results to Forecast Future
Sample Results
Using Sample Results to Forecast a
Future Sample Average
Using Sample Results to Forecast a
Future Sample Proportion
Summary 198
Chapter 13 Time-Series Forecasting
Basic Approaches for
One-Period Forecasts
Simple Approaches
Moving Average
Smoothed Average
Comparison of Forecasts
Precision
Bias
Exploiting Multiperiod Patterns
Treating Seasonality
Deseasonalizing a Time Series
Forecasting the
Deseasonalized Series
Reseasonalizing the Forecast
Generating the Probability
Distribution Forecast
Decomposition of Time Series
into Seasonality and
Trend Components
Separating out Seasonality
Extrapolating Trend and
Cycle Components
Holt's Model: Exponential Smoothing
with Trend
Winter's Model: Exponential Smoothing
with Trend and Seasonality
Other Advanced Techniques
Considerations in Preparing and Using
a Forecast
Chapter 14 Regression: Forecasting
Using Explanatory Factors
The Simple Linear Model
Fitting the Model Using
"Least Squares"
Important Properties ofthe Least-Squares
Regression Line
Summary Regression Statistics
Standard Error of Estimate
Adjusted R Square
Standard Error of the Coefficients
Assumptions behind the l .inear
Regression Model
Linearity
Independence
Homoscedasticit"
Normality
Summary of
Regression Assumptions
Model-Building Philosophy
Uses ofthe Linear Model
Nature ofthe Relationship
among Variables
The Importance ofthe Underlying
Relationship to the Use of
the Model
Model-Building Procedure
Common Mistakes
Summary
Forecasting Using the Linear
Regression Model
Point Forecast
Interval Forecast
Analogy to Simole Random
Sampling
Using Dummy Variables to Represent
Categorical Variables
Example
Dummy Variables for More than
Two Groups
Useful Data Transforrmations
Example
Choosing a Transformation
Transforming the Y-Variable
Chapter 15 Discrete-Event
Simulation
An Example Application of
Discrete-Event Simulation
The Model
Important Issues in Discrete-
Event Simulation
Calibrating the Uncertainties
Validating the Model
Avoiding Peculiarities Associated with
Start-up
Terminating the Model Run
Summary
Chapter 16 Introduction to
Optimization Models
Transforming an Evaluation Model into an
Optimization Model
Example l: Optimal Order
Quantity
Example 2: Product Mix Planning
Example 3: Facility Location
Summary ofExamples
Categorizing and Solving Optimization
Models
Example l: Nonlinear Programming
Example 2: Linear Programming
Example 3: Integer Programming
Uncertainty in Optimization Models:
Sensitivity Analysis
Lagrange Multipliers
Linear Programming Models
Building an Optimization Model
from Scratch
Chapter 17 The Mathematics
of Optimization
Algebraic Framework for
Optimization Models
Functions
General Structure of an
Optimization Model
Integer Programming
Linear Programnung (LP)
Graphical Representation of
Example 2
The Simplex Algorithm
Some Final Comments on the Simplex
Algorithm and LP
Karmarkar's Algorithm: An Alternative
Approach to Solving
LP Models
Nonlinear Programming (NLP)
Levers to Control the GS
Solution Approach
Integer Programming (IP)
Final Observations: LP, NLP, and IP
Summary
Cases
Case l: American Lawbook
Corporation (A)
Case 2: American Lawbook
Corporation (B)
Case 3: Amore Prozen Foods
Case 4: Athens Glass Works
Case 5: Buckeye Power & Light
Company
Case 6: Buckeye Power & Light
Company Supplement
Case 7: California Oil Company
Case 8: C.K. Coolidge, Inc. (A)
Case 9: The Commerce Tavern
Case lO: CyberLab: A New Business
Opportunity for PRlCO (A)
Case ll: CyberLab: Supplement
Case 12: CyberLab: A New Business
Opportunity for PRlCO (B)
Case 13: Dhahran Roads (A)
Case 14 Dhahran Roads (B)
Case 15: Discounted Cash1
Flow Exercises
Case 16, Edgcomb Metals (A)
Case l7: Florida Glass Company (A)
Case 18: Florida Glass Company (A)
Supplement
Case 19: Foulke Consumer
Products, Inc.
Case 20: Foulke Consumer
Products, Inc., Supplement
Case 21: Freemark Abbey Winery
Case 22: Galaxy Micro Systems
Case 23: Galaxy Micro Systems
Supplement
Case 24: George's T-Shirts
Case 25: Harimann International
Case 26: Hightower Department Stores:
Imported Stuffed Animals
Case 27: International Guidance
and Controls
Case 28: Jade Shampoo (A)
Case 29: Jade Shampoo (B)
Case 30: Jaikumar Textiles, Ltd.'
The Nylon Division (A)
Case 31: Jaikumar Textiles, Ltd.:
The Nylon Division (B)
Case 32: Lesser Antilles Lines: The Island
of San Huberto
Case 33: Lightweight Aluminum
Company: The Lebanon Plant
Case 34: Lorex Pharmaceuticals
Case 35: Maxco, Inc., and the
Gambit Company
Case 36: The Oakland A's (A)
Case 37: The Oakland A's (A)
Supplement
Case38:TheOaklandA's(B)
Case 39: Piedmont Airlines:
Discount Seat Allocation (A)
Case 40: Piedmont Airlines:
Discount Seat Allocation (B)
Case 41: Probability Assessment
Exercise
Case 42: Problems in Regression
Case 43: Roadway Construction
Company
Case 44: Shumway, Horch, and
Sager(A)
Case 45: Shumway, Horch, and
Sager (B)
Case 46: Sleepmore Mattress
Manufacturing: Plant
Consolidation
Case 47: Sprigg Lane (A)
Case 48: T. Rowe Price Assoclates
Case 49: Wachovia Bank and Trust
Company, N.A. (B)
Case 50: Wachovia Bank and Trust
Company, N.A. (B): Supplement
Case 51: Waite First Securities
Case 52: The WaldorfProperty
· · · · · · (收起)
Chapter l Proactive
Decision Making
Routine Decisions
The Challenges of Proactive
Decision Making
Alternatives
Assumptions-Structure
Assumptions-Assessments
Performance
Summary
Chapter 2 Alternatives
Small Number of Alternatives
Sequential Decisions
A Single Decision Quantity
Two or More Decision Quantities
Decision Rules
Summary
Chapter 3 Structuring Assumptions
in Decision Making
Structuring Relationships llsing an
Influence Diagram
Structuring a Sequence of Decisions
and Uncertainties Using a
Decision Tree
Influence Diagrams with
Uncertain Quantities
Final Examples of How to Develop an
Influence Diagram
The Use oflnfluence Diagrams and
Decision Trees
Case: Destiny Consulting Group
Chapter 4 Assessment
Sensitivity Analysis
The Language of Probability
Uncertainties with a Pew
Potential Outcomes
Uncertainties with Many
Potential Outcomes
Summary Measures of
Probability Distributions
Deriving the Probability Distribution
for Performance
Summary
Chapter 5 Performance
Relevant Monetary Flows
Evaluating Alternatives
under Uncertainty
Few Potential Outcomes
Many Potential Outcomes
Summary
Chapter 6 Risk Management
Value of Information
Perfect Information
Imperfect Information
Value of Control
Perfect Control
Control ofContinuously
Ranging Quantities
Adding Value and Reducing Risk
Summary
Chapter 7 Evaluating
Multiperiod Performance
Cash Flow
An Example
Time Value of Money '
Accumulated Value
Present Value and Net Present Value
Formulas for Accumulated and Present
Value Calculations
Streams in Perpetuity
Pretax versus Aftertax Analyses
The Reinvestment Rate
Hurdle Rate
Internal Rate ot Return
Nominal versus Effective Rates
of Return
Chapter 8 Multiobjective and
Multistakeholder Choice
The Generic Choice Problem
Example
First-Rbund Eliminations
Dominance
Decision Rules without Trade-
offJudgments
The Lexicographic Rule
Satisficing
Rate and Weight: Lin"'"' Additive
Scoring Rules
Rating Alternatives
Weighting Attributes
Assumptions ofRate and Weight
Multiple Stakeholder Problems
Appendix l Comments on the
Dependence ofWeights on the
Scaling of Attributes
Exercises
Chapter 9 Risk Preference
and Utility
The Utility of
Monetary Consequences
Risk Aversion
Constant Risk Aversion: Negative
Exponential Utility
Decreasing Risk Aversion:
Logarithmic Utility
Using a Utility Curve for Risk
Analysis
Separation of Risk-Return and Mean-
Variance Analysis
Corporate Risk Policy
Exercises
Chapter lO Competitor Analysis
Characterizing Competitive
Situations
Matrix Format
Classical Structures
No (or Little) Conflict
Prisoner's Dilemma
Preemption
Summary
Chapter ll Probability
Distributions
The Language ofProbability
Distributions
The Probability Mass Function
The Cumulative Distribution
Function - .,
Continuous and Many-Valued
Uncertain Quantities
Assessment: Capturing Personal
Judgment
An Example of Assessing a
Probability Distribution
Assessment: Using Historical Data as
a Guide
Identifying Suitable Data
Using the Suitable Data as a Guide
Adjusting Data for One
Distinguishing Factor
Assessment: Appealing to Underlying
Structure
The Binomial Distribution
The Normal Distribution
The Poisson Distribution
The Exponential Distribution
Subjective Biases and Assessment
Summary
Chapter 12 Sampling
Forecasting Sample Results
Forecasting a Sample Average
Forecasting a Sample Proportion
Using Sample Results to Draw
Inferences about the Underlying
Probability Distribution
Inferences about the Mean of
the Underlying Probability
Distribution
Inferences about the
Underlying Probability
Using Sample Results to Forecast Future
Sample Results
Using Sample Results to Forecast a
Future Sample Average
Using Sample Results to Forecast a
Future Sample Proportion
Summary 198
Chapter 13 Time-Series Forecasting
Basic Approaches for
One-Period Forecasts
Simple Approaches
Moving Average
Smoothed Average
Comparison of Forecasts
Precision
Bias
Exploiting Multiperiod Patterns
Treating Seasonality
Deseasonalizing a Time Series
Forecasting the
Deseasonalized Series
Reseasonalizing the Forecast
Generating the Probability
Distribution Forecast
Decomposition of Time Series
into Seasonality and
Trend Components
Separating out Seasonality
Extrapolating Trend and
Cycle Components
Holt's Model: Exponential Smoothing
with Trend
Winter's Model: Exponential Smoothing
with Trend and Seasonality
Other Advanced Techniques
Considerations in Preparing and Using
a Forecast
Chapter 14 Regression: Forecasting
Using Explanatory Factors
The Simple Linear Model
Fitting the Model Using
"Least Squares"
Important Properties ofthe Least-Squares
Regression Line
Summary Regression Statistics
Standard Error of Estimate
Adjusted R Square
Standard Error of the Coefficients
Assumptions behind the l .inear
Regression Model
Linearity
Independence
Homoscedasticit"
Normality
Summary of
Regression Assumptions
Model-Building Philosophy
Uses ofthe Linear Model
Nature ofthe Relationship
among Variables
The Importance ofthe Underlying
Relationship to the Use of
the Model
Model-Building Procedure
Common Mistakes
Summary
Forecasting Using the Linear
Regression Model
Point Forecast
Interval Forecast
Analogy to Simole Random
Sampling
Using Dummy Variables to Represent
Categorical Variables
Example
Dummy Variables for More than
Two Groups
Useful Data Transforrmations
Example
Choosing a Transformation
Transforming the Y-Variable
Chapter 15 Discrete-Event
Simulation
An Example Application of
Discrete-Event Simulation
The Model
Important Issues in Discrete-
Event Simulation
Calibrating the Uncertainties
Validating the Model
Avoiding Peculiarities Associated with
Start-up
Terminating the Model Run
Summary
Chapter 16 Introduction to
Optimization Models
Transforming an Evaluation Model into an
Optimization Model
Example l: Optimal Order
Quantity
Example 2: Product Mix Planning
Example 3: Facility Location
Summary ofExamples
Categorizing and Solving Optimization
Models
Example l: Nonlinear Programming
Example 2: Linear Programming
Example 3: Integer Programming
Uncertainty in Optimization Models:
Sensitivity Analysis
Lagrange Multipliers
Linear Programming Models
Building an Optimization Model
from Scratch
Chapter 17 The Mathematics
of Optimization
Algebraic Framework for
Optimization Models
Functions
General Structure of an
Optimization Model
Integer Programming
Linear Programnung (LP)
Graphical Representation of
Example 2
The Simplex Algorithm
Some Final Comments on the Simplex
Algorithm and LP
Karmarkar's Algorithm: An Alternative
Approach to Solving
LP Models
Nonlinear Programming (NLP)
Levers to Control the GS
Solution Approach
Integer Programming (IP)
Final Observations: LP, NLP, and IP
Summary
Cases
Case l: American Lawbook
Corporation (A)
Case 2: American Lawbook
Corporation (B)
Case 3: Amore Prozen Foods
Case 4: Athens Glass Works
Case 5: Buckeye Power & Light
Company
Case 6: Buckeye Power & Light
Company Supplement
Case 7: California Oil Company
Case 8: C.K. Coolidge, Inc. (A)
Case 9: The Commerce Tavern
Case lO: CyberLab: A New Business
Opportunity for PRlCO (A)
Case ll: CyberLab: Supplement
Case 12: CyberLab: A New Business
Opportunity for PRlCO (B)
Case 13: Dhahran Roads (A)
Case 14 Dhahran Roads (B)
Case 15: Discounted Cash1
Flow Exercises
Case 16, Edgcomb Metals (A)
Case l7: Florida Glass Company (A)
Case 18: Florida Glass Company (A)
Supplement
Case 19: Foulke Consumer
Products, Inc.
Case 20: Foulke Consumer
Products, Inc., Supplement
Case 21: Freemark Abbey Winery
Case 22: Galaxy Micro Systems
Case 23: Galaxy Micro Systems
Supplement
Case 24: George's T-Shirts
Case 25: Harimann International
Case 26: Hightower Department Stores:
Imported Stuffed Animals
Case 27: International Guidance
and Controls
Case 28: Jade Shampoo (A)
Case 29: Jade Shampoo (B)
Case 30: Jaikumar Textiles, Ltd.'
The Nylon Division (A)
Case 31: Jaikumar Textiles, Ltd.:
The Nylon Division (B)
Case 32: Lesser Antilles Lines: The Island
of San Huberto
Case 33: Lightweight Aluminum
Company: The Lebanon Plant
Case 34: Lorex Pharmaceuticals
Case 35: Maxco, Inc., and the
Gambit Company
Case 36: The Oakland A's (A)
Case 37: The Oakland A's (A)
Supplement
Case38:TheOaklandA's(B)
Case 39: Piedmont Airlines:
Discount Seat Allocation (A)
Case 40: Piedmont Airlines:
Discount Seat Allocation (B)
Case 41: Probability Assessment
Exercise
Case 42: Problems in Regression
Case 43: Roadway Construction
Company
Case 44: Shumway, Horch, and
Sager(A)
Case 45: Shumway, Horch, and
Sager (B)
Case 46: Sleepmore Mattress
Manufacturing: Plant
Consolidation
Case 47: Sprigg Lane (A)
Case 48: T. Rowe Price Assoclates
Case 49: Wachovia Bank and Trust
Company, N.A. (B)
Case 50: Wachovia Bank and Trust
Company, N.A. (B): Supplement
Case 51: Waite First Securities
Case 52: The WaldorfProperty
· · · · · · (收起)
读后感
用户评价
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