The Oxford handbook of agent-based computational management science / edited by Friederike Wall, Shu-Heng Chen, Stephan Leitner.

Format
Book
Language
English
Εdition
1st ed.
Published/​Created
Oxford : Oxford University Press, 2024-
Description
1 online resource : illustrations.

Details

Subject(s)
Editor
Series
Oxford handbooks online. [More in this series]
Frequency
Monthly
Summary note
This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online.
Bibliographic references
Includes bibliographical references.
Source of description
  • Description based on online resource; title from home page (viewed on February 14, 2024).
  • Description based on publisher supplied metadata and other sources.
Contents
  • Cover
  • Half Title
  • Title Page
  • Copyright Page
  • Table of Contents
  • Acknowledgements
  • Contributors
  • Chapter 1 Agent-Based Modelling for Bridging the Micro-Macro Divide in Management Science An Introduction
  • 1. Introduction
  • 2. On the Micro-Macro Divide in Management Science
  • 2.1. Issues and Promises
  • 2.2. Linking the Micro Level and Macro Level
  • 3. Agent-Based Computational Management Science as a Candidate to Bridge the Micro-Macro Divide
  • 3.1. Reciprocity of Micro-Macro Links and Framework of a Generative Model
  • 3.2. The Agent-Based Paradigm as a Generative Approach to the Micro-To-Macro Problem
  • 3.3. Conceptualization of Agents
  • 4. 'Technical' Aspects of Agent-Based Computational Management Science
  • 4.1. Introductions to Agent-Based Modelling and Simulation
  • 4.2. Prominent 'Structured' Approaches for Agent-Based Models in Management Science
  • 4.3. Some Remarks On the Implementation of Agent-Based Models
  • 5. A Brief Overview of the Handbook
  • 5.1. Microfoundations of Agent-Based Models in Management
  • 5.2. Agent-Based Modelling and Simulation for Theory Building in Management
  • 5.3. Agent-Based Modelling and Simulation for Operational Issues in Management
  • 5.4. Reflections and Extensions
  • PART I MICROFOUNDATIONS OF AGENT-BASED MODELS IN MANAGEMENT
  • Chapter 2 Bounded Rationality: Foundations and Varieties in Agent-Based Modelling
  • 1. Motivation
  • 2. Mirroring Principle: Breaking the Asymmetry
  • 2.1. Bounded Rationality in EBM and ABM
  • 2.2. Bounded Models With Full Rationality
  • 2.3. Unbounded Models With Bounded Rationality
  • 2.4. Dwarfing
  • 2.5. Summary
  • 3. Darwinism and Bounded Rationality
  • 3.1. Two Kinds of Canonical ABM
  • 3.2. Bounded Rationality in the Evolutionary Context
  • 3.3. Bounded Rationality in the Computational Context
  • 3.4. Modularity Principle.
  • 3.5. Social and Crowd Psychology
  • 3.6. Summary
  • 4. Physics and Bounded Rationality
  • 4.1. Zero-Intelligence Agents
  • 4.2. Entropy Maximization Principle
  • 4.3. 'Dumb' Agents
  • 4.4. Summary
  • 5. Concluding Remarks
  • Chapter 3 Artificial Cognition
  • 2. Evidence Theory and Belief Functions
  • 3. Q-Analysis of Simplicial Families
  • 4. Unsupervised Neural Networks
  • 5. A Connectionist Conclusion
  • Chapter 4 Pick Up the Slack: Modelling Resource Availability and Search Processes in Organizations
  • 2. Slack Resources and Search in Agent-Based Models
  • 2.1. Single-Agent Models
  • 2.2. Multiagent Models
  • 3. Slack Resources and Search in Empirical Research
  • 3.1. Operationalizing Slack Resources
  • 3.2. Main Findings
  • 4. Open Questions and Future Directions
  • 4.1. Performance Fluctuations and the Accumulation of Slack Resources
  • 4.2. Slack Resources and Nonlinear Search Patterns
  • 4.3. Slack Resources and Performance Outcomes
  • 4.4. Slack Resources and Organizational Architecture
  • PART II AGENT-BASED MODELLING AND SIMULATION FOR THEORY BUILDING IN MANAGEMENT
  • Chapter 5 Agent-Based Modelling for Strategy
  • 2. ABM in Strategy Research and Management: A Brief Overview
  • 2.1. Origins
  • 2.2. Growth
  • 2.3. ABM Versus Closed-Form Analytical Modelling
  • 2.4. ABM and Theory Development
  • 2.5. Distinctive Advantages of ABM
  • 2.6. Inherent Challenges Related to ABM
  • 3. Applications of ABM in Strategy Research
  • 4. Advantages and Limitations of ABM in Strategy Research
  • 4.1. Advantages
  • 4.2. Limitations
  • 5. Trajectories for Application of ABM in Strategy Research
  • 6. Conclusion
  • Chapter 6 Agent-Based Modelling in Innovation Management
  • 2. Recent Uses
  • 2.1. Literature Search and Choice of Articles.
  • 2.2. Diffusion of Innovation
  • 2.2.1. Consumer Targeting
  • 2.2.2. Social Identity
  • 2.2.3. Supply Constraints
  • 2.2.4. Product Design
  • 2.2.5. Entrepreneurship
  • 2.2.6. Governmental Interventions
  • 2.2.7. Social Culture
  • 2.2.8. Management Education
  • 2.3. Organization and Information Flows
  • 2.3.1. Innovation Process
  • 2.3.2. R&amp
  • D Collaboration
  • 3. Promising Features
  • 3.1. Agents
  • 3.1.1. Heterogeneity
  • 3.1.2. Individuality
  • 3.1.3. Uncertainty
  • 3.2. Environment and Interactions
  • 3.2.1. Competitors
  • 3.2.2. Product Portfolio
  • 3.2.3. Marketing Measures
  • 3.2.4. Peer Effects
  • 3.2.5. Social Network
  • 3.2.6. Parameterization and Calibration
  • 3.3. Mixed Methods
  • 3.3.1. Scenario Analysis
  • 3.3.2. Artificial Intelligence
  • 4. Promising Applications
  • 4.1. Novel Products and Services
  • 4.1.1. Research and Development
  • 4.1.2. Business Model Innovations
  • 4.1.3. Two-Sided Digital Platforms
  • 4.2. Organizational Issues
  • 4.2.1. Promoting Information Exchange
  • 4.2.2. Incentivizing Innovativeness
  • 4.2.3. Reorganizing
  • 4.3. Rising Markets
  • 4.3.1. Smart Products
  • 4.3.2. Sustainable Products
  • 4.3.3. AI Products
  • 5. Conclusion
  • Chapter 7 Agent-Based Modelling in Marketing: Interactions Are King
  • 2. Why Is ABM a Good Approach for Marketing?
  • 3. Applications of ABM in Marketing
  • 3.1. General Reviews of ABM in Marketing
  • 3.2. Diffusion of Information/Innovations
  • 3.3. Strategy and Interfirm Relationships
  • 3.4. Marketing Mix
  • 3.5. Consumer Behaviour
  • 4. Challenges and Limitations of ABM in Marketing
  • 5. Future Uses of ABM in Marketing
  • Chapter 8 Theory Building in Organization Science With Agent-Based Computational Models: Past, Present, and Future
  • 2. On Theory Building in General.
  • 3. Methodological Individualism and Theory Building in Organizational Science
  • 4. A Historical Overview of Formal Theory Building in Organizational Economics
  • 4.1. Theory of the Firm: Scale and Scope of the Firm
  • 4.2. Theory of Internal Organization: Organization of Activities Within the Firm
  • 5. ABM Approach for Theory Building
  • 5.1. Early Works
  • 5.2. Organizational Learning as Adaptive Search
  • 5.3. Organizational Structure
  • 6. Discussion and Conclusion
  • Chapter 9 Interorganizational Network Formation: An Agent-Based Perspective
  • 2. Defining Interorganizational Networks
  • 3. Network Emergence and Network Formation
  • 4. The Complexity of Interorganizational Networks
  • 4.1. An Example of Interorganizational Network Formation
  • 5. Conclusions
  • Chapter 10 Using Agent-Based Modelling for Theory Building in Organizational Routines
  • 2. A Brief Overview of Organizational Routines
  • 2.1. The Development of the Concept
  • 2.2. Routine Dynamics and Its Cutting-Edge Trends
  • 3. Contemporary Use of ABM in Organizational Routines
  • 3.1. The Goal and Intended Purposes of ABM
  • 3.1.1. Illustration
  • 3.1.2. Description
  • 3.1.3. Theoretical Exposition
  • 3.1.4. Explanation
  • 3.1.5. Prediction
  • 3.2. Challenges That ABM Encounters
  • 3.2.1. The Appropriate Level of Model Complicatedness
  • 3.2.2. Entities and the Granularity of Analysis
  • 3.2.3. The Transparency, Accuracy, and Credibility of Models
  • 4. Potential Directions of Future Work
  • Chapter 11 Modelling the Leadership Influence Process
  • 1. The Promise and Challenges of Modelling Leadership
  • 1.1. Leadership Properties Observable in ABM Modelling and Simulation
  • 1.1.1. Modelling the Factual Dynamics Versus Normative Attribution of Leadership.
  • 1.2. Leader-Tagging: Localized Perception of Signalling About Who Is Leading
  • 1.3. Modelling Leadership as Well-Defined Network Structure and Dynamics
  • 1.3.1. Example: The Emergence of Leadership During Self-Organization in Complex Networks
  • 1.3.2. Agent-Based Modelling of the Leadership Influence Process-The Basics
  • 2. The State of the Art
  • 2.1. Trail Blazers-Early Computer Models of Leadership
  • 2.1.1. The Leader-Follower Relationship
  • 2.1.2. Cognitive Demand and Optimal Organization Design
  • 2.1.3. Advice Networks, Game Theory, the Emergence of Hierarchy, Status, and Social Power
  • 2.1.4. Social Cognition in the Animal Kingdom as Well as Human Organizing
  • 2.2. Representing Leadership as Structures That Signal Expectancy Alignment
  • 2.2.1. Model Description: Searching Opportunity Landscape to Build a Shared Mental Model
  • 2.2.2. Results From Selected Studies
  • 2.2.3. The Effects of Individual Agent Memory When Aligning Expectations
  • 2.2.4. Aligning Expectations in Virtual Versus Face-To-Face Teams
  • 2.2.5. Aligning Expectations in Larger Collectives
  • 2.2.6. Expectancy Alignment Beyond the Team: The State of the Art
  • 2.2.7. Representing Leadership as Reinforcing Localized Instrumental Momentum
  • 2.2.8. Task Implementation and Practice Improvement in the Nursing Sector
  • 2.2.9. The Impact of Ambivalent Opinion Leaders in Political Movements
  • 2.2.10. Building Instrumental Momentum With a Small Team: The State of the Art
  • 2.3. Representing Leadership as Emergent Cooperating Valence
  • 2.3.1. Modelling Bottom-Up Collective Intelligence and the Leadership Influence Process
  • 2.3.2. ABM Using Economic Game Theory Payoffs as Feedback for Learning
  • 2.3.3. Adaptive Agent and Adaptive Environment as Ingredients of Emergent Intelligence
  • 2.3.4. Emergence/Inhibition of Free Riders.
  • 2.3.5. Emergent of Leadership-Followership.
Other title(s)
Agent-based computational management
ISBN
  • 0-19-766813-5
  • 0-19-766814-3
  • 0-19-766815-1
OCLC
  • 1422535501
  • 1565283602
Doi
  • 10.1093/oxfordhb/9780197668122.001.0001
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