Adaptive coordination of a learning team
Management Science
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Adaptation on rugged landscapes
Management Science
Design Rules: The Power of Modularity Volume 1
Design Rules: The Power of Modularity Volume 1
Recombinant Uncertainty in Technological Search
Management Science
Imitation of Complex Strategies
Management Science
Problem-Solving Oscillations in Complex Engineering Projects
Management Science
Overcoming Local Search Through Alliances and Mobility
Management Science
Modularity and Innovation in Complex Systems
Management Science
From T-Mazes to Labyrinths: Learning from Model-Based Feedback
Management Science
A Knowledge-Based Theory of the Firm--The Problem-Solving Perspective
Organization Science
Speed and Search: Designing Organizations for Turbulence and Complexity
Organization Science
Human Problem Solving
Two Faces of Search: Alternative Generation and Alternative Evaluation
Organization Science
The Value of Moderate Obsession: Insights from a New Model of Organizational Search
Organization Science
Patterned Interactions in Complex Systems: Implications for Exploration
Management Science
Hierarchical Structure and Search in Complex Organizations
Management Science
| Hi-index | 0.00 |
Organizations are frequently faced with high levels of complexity. While the importance of search for dealing with complex systems is widely acknowledged, how organizations should structure their search processes remains largely unexplored. This paper starts to address basic questions: How much of the entire system, and thus complexity, should be taken into consideration at any given time during a search process? Should a problem solver pursue an integrated search and be concerned with the whole system right from the start, or should a problem solver incrementally expand the “search domain,” i.e., the subset of system elements and interdependencies that are included in the search efforts? If the latter, how “chunky” should these steps be? Our analysis of a simulation model yields four insights: 1 expanding the search domain in smaller steps can yield a distinct advantage in final system performance, 2 following a completely incremental expansion pattern is not necessary as long as larger chunks are added early on in the process, 3 the value of chunky search is particularly high if highly influential system elements are considered first and highly dependent elements are added later, and 4 under time pressure, chunky search can lose its performance advantage over more integrated search processes. We discuss the implications of our findings for managing organizational search and complex systems more broadly.