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The Handbook of Behavioral Operations
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Newark :
John Wiley & Sons, Incorporated,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Intro; Title Page; Copyright Page; Contents; List of Contributors; Preface; Part I Methodology; Chapter 1 Designing and Conducting Laboratory Experiments; 1.1 Why Use Laboratory Experiments?; 1.2 Categories of Experiments; 1.3 Some Prototypical Games; 1.3.1 Individual Decisions; 1.3.2 Simple Strategic Games; 1.3.3 Games Involving Competition: Markets and Auctions; 1.4 Established Good Practices for Conducting BOM Laboratory; 1.4.1 Effective Experimental Design; 1.4.2 Context; 1.4.3 Subject Pool; 1.5 Incentives; 1.6 Deception; 1.7 Collecting Additional Information
- 1.8 Infrastructure and LogisticsReferences; Chapter 2 Econometrics for Experiments; 2.1 Introduction; 2.2 The Interaction Between Experimental Design and Econometrics; 2.2.1 The Average Treatment Effect; 2.2.2 How to Achieve Randomization; 2.2.3 Power Analysis; 2.3 Testing Theory and Other Hypotheses: Classical Hypothesis Testing; 2.3.1 Tests on Continuous Response Data; 2.3.1.1 Parametric Tests; 2.3.1.2 Nonparametric Tests; 2.3.1.3 Testing for Trends; 2.3.1.4 Bootstrap and Permutation Tests; 2.3.1.5 An Illustration from Davis et al. (2011); 2.3.1.6 When to Use Nonparametric Tests
- 2.3.2 Tests on Discrete Response Data2.4 Testing Theory and Other Hypotheses: Regression Analysis; 2.4.1 Ordinary Least Squares: An Example from Davis et al. (2011); 2.4.2 Panel Data Methods; 2.4.2.1 Dynamic Panel Data Models: The Example of Demand Chasing; 2.4.3 Limited Dependent Variable Models; 2.4.3.1 Binary Response Data; 2.4.3.2 Censored Data; 2.4.3.3 Other Data; 2.5 Dependence of Observations; 2.5.1 A "Conservative" Approach; 2.5.2 Using Regressions to Address Dependence; 2.5.2.1 Higher Level Clustering; 2.5.2.2 How Many Clusters; 2.6 Subject Heterogeneity
- 2.6.1 Multilevel Analysis: Example Implementation2.7 Structural Estimation; 2.7.1 Model Selection; 2.7.2 An Illustration; 2.7.3 A Word on Standard Errors; 2.7.4 Subject Heterogeneity: Finite Mixture Models; 2.8 Concluding Remarks; Acknowledgments; References; Chapter 3 Incorporating Behavioral Factors into Operations Theory; 3.1 Types of Behavioral Models; 3.1.1 Nonstandard Preferences; 3.1.2 Nonstandard Decision-making; 3.1.3 Nonstandard Beliefs; 3.2 Identifying Which Behavioral Factors to Include; 3.2.1 Robustly Observed; 3.2.2 One/A Few Factors Explain Many Phenomena
- 3.2.3 Boundaries and Observed Behavioral Factors3.3 Nesting the Standard Model; 3.3.1 Reference Dependence; 3.3.2 Social Preferences and Comparison; 3.3.3 Quantal Response Equilibrium; 3.3.4 Cognitive Hierarchy in Games; 3.3.5 Learning; 3.3.6 Overconfidence; 3.4 Developing Behavioral Operations Model; 3.4.1 Parsimony Is Still Important; 3.4.2 Adding One Versus Many Behavioral Factors; 3.5 Modeling for Testable Predictions; References; Chapter 4 Behavioral Empirics and Field Experiments; 4.1 Going to the Field to Study Behavioral Operations