Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

181
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
181
Impact of Individuals on a Group01:25

Impact of Individuals on a Group

21
In social psychology, the interplay between individuals and groups is a central concern, particularly regarding how individual actions and characteristics influence group processes and outcomes. While much research emphasizes the group's power in shaping individual behavior, it is equally significant to understand how individuals contribute to the functioning, development, and success of groups.Individual Roles in Group Productivity and Decision-MakingIndividuals are not passive participants in...
21
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

274
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
274
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

91
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
91
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

109
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
109
Predicting Products: Substitution vs. Elimination02:52

Predicting Products: Substitution vs. Elimination

12.4K
When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
12.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Theorizing competition: An interdisciplinary framework.

Competition & change·2025
Same author

Corporate power and global value chains: current approaches for conceptualizing the power of multinationals.

Review of evolutionary political economy·2024
Same author

Trust and Social Control: Sources of Cooperation, Performance, and Stability in Informal Value Transfer Systems.

Computational economics·2021
Same journal

Cooperative protection against stochastic losses: Experimental evidence on behavioral dynamics.

Journal of evolutionary economics·2026
Same journal

Mercantilist and protectionist shocks on innovation, growth, and economic policy in European regions.

Journal of evolutionary economics·2026
Same journal

Financial production and the subprime mortgage crisis.

Journal of evolutionary economics·2023
Same journal

Robotization, employment, and income: regional asymmetries and long-run policies in the Euro area.

Journal of evolutionary economics·2023
Same journal

V for vaccines and variants.

Journal of evolutionary economics·2023
Same journal

The impact of artificial intelligence on labor markets in developing countries: a new method with an illustration for Lao PDR and urban Viet Nam.

Journal of evolutionary economics·2023
See all related articles

Related Experiment Video

Updated: Sep 29, 2025

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.0K

Capability accumulation and product innovation: an agent-based perspective.

Claudius Gräbner1,2,3, Anna Hornykewycz1

  • 1Institute for the Comprehensive Analysis of the Economy (ICAE), Johannes Kepler University Linz, Linz, Austria.

Journal of Evolutionary Economics
|March 21, 2022
PubMed
Summary
This summary is machine-generated.

Firms build capabilities by producing diverse, related products. Product complexity and relatedness significantly impact innovation dynamics, influencing evolutionary macroeconomics.

Keywords:
Agent-based modelingCapabilitiesComplexityInnovationLearning

More Related Videos

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.0K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.5K

Related Experiment Videos

Last Updated: Sep 29, 2025

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

6.0K
Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.0K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.5K

Area of Science:

  • Evolutionary Macroeconomics
  • Innovation Studies
  • Agent-Based Modeling

Background:

  • Existing literature highlights capability accumulation's role in innovation.
  • Evolutionary macroeconomic models often focus on process innovation, neglecting product innovation in the final consumption good sector.

Purpose of the Study:

  • Introduce an agent-based model to study product heterogeneity and relatedness.
  • Analyze the implications of product space topology on firm capabilities and innovation.
  • Integrate microeconomic insights on product innovation into macroeconomic models.

Main Methods:

  • Developed a simple agent-based model (ABM) for firm capability accumulation.
  • Simulated firms producing heterogeneous and related final consumption goods.
  • Explored different 'product spaces' to analyze topological structures.

Main Results:

  • Product space topology significantly influences innovation dynamics.
  • The relationship between product complexity and centrality affects capability accumulation.
  • Product complexity plays a nontrivial role in price-setting dynamics.

Conclusions:

  • The structure of product relatedness is crucial for understanding innovation.
  • Further research in evolutionary macroeconomics should incorporate product complexity and space topology.
  • The proposed agent-based model can serve as an innovation module for macroeconomic analysis.