Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation

By Michael J. North, Charles M. Macal. 2007

850 citations recorded by the source corpus.

Subfields: Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a8aafdf4eb2987c808ee268d055bd440648bf60b

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In Management Information Systems

In Strategy and Management

Citations in the corpus

Facilitating Parameter Estimation and Sensitivity Analysis of Agent-Based Models: A Cookbook Using NetLogo and 'R' (2014, methodology): “This issue is often addressed in textbooks about agent-based modelling (e.g., North & Macal 2007; Railsback & Grimm 2012; Squazzoni 2012; Tesfatsion & Judd 2006).”
A Survey of Agent-Based Modeling Practices (January 1998 to July 2008) (2009, background): “A fair amount of research in this area has already been done (for a few examples see Axtell, Axelrod, Epstein and Cohen 1996; Bonabeau 2002; Epstein and Axtell 1996; Epstein 1999; Macal and North 2006; Miller and Page 2007; North and Macal 2007).”
Everything you need to know about agent-based modelling and simulation (2016, background): “Some well-cited introductory material on ABMS includes Axelrod and Tesfatsion (2016), Bonabeau (2001), Gilbert (2008), Gilbert and Troitzsch (2005), Helbing and Balietti (2011), Railsback and Grimm (2011), Wilensky and Rand (2015), and North and Macal (2007).”
Networks, ecosystems, fields, market systems? Making sense of the business environment (2020, neutral): “…the following methods and approaches that seem to hold promise in researching complex and systemic business environments: agent-based modeling (cf., North & Macal, 2007), causal process tracing (cf., Blatter & Haverland, 2012), action research (cf., Abrahamsen, Henneberg, Huemer, & Naudé, 2016;…”
Embracing Complexity and Uncertainty: The Potential of Agent-Based Modeling for Environmental Planning and Policy (2008, methodology): “North and Macal (2007) also recommend ensuring that the model fits with the questions it is meant to answer and that the data used in the model are validated, and assessing the validity of the theory informing the model and how it is implemented.”
An agent‐based model of farmer decision‐making and water quality impacts at the watershed scale under markets for carbon allowances and a second‐generation biofuel crop (2011, background): “To date, ABM has been applied to a wide range of disciplines, including ecological modeling [Grimm and Railsback, 2005], urban development [Batty, 2005], business and finance [Ehrentreich, 2008; North and Macal, 2007], and energy policy [Wittmann, 2008].”
Discrete-event simulation is dead, long live agent-based simulation! (2010, methodology): “This multi-step approach to building models is what we recommend in the book that I wrote with Michael North (North and Macal, 2007): Start out by using what you know and what you have, and build the model through phases.”
Agent-Based Modeling in Marketing: Guidelines for Rigor (2011, methodology): “It has been said that before amodel undergoes verification and validation, it is just a toy; after a model undergoes verification and validation, it is a tool (North & Macal, 2007).”
Agent Based Modelling and Simulation tools: A review of the state-of-art software (2017, background): “particularly applied in the case of modelling complex phenomena, where a lot of agents or active entities interact among each other with certain inherent attributes to establish agency relationships, thereby facilitating automated reasoning and problem-solving [34, 35].”