An innovative application of event structure analysis (ESA)

Area of Science:

• Management Science
• Engineering Management
• Innovation Management

Background:

• Event Structure Analysis (ESA) is a valuable method for process research.
• Existing ESA methods can be enhanced for more robust causal inference and quantitative pattern exploration.

Purpose of the Study:

• To present an innovative application and enhancement of Event Structure Analysis (ESA).
• To integrate causal process tracing tests and network analyses with ESA.
• To propose and exemplify new analytical approaches for event network models.

Main Methods:

• Developed a robust system for coding events.
• Utilized causal process tracing tests for inferring necessary causal connections.
• Combined ESA with network analyses for quantitative pattern exploration.
• Proposed five types of analysis for event network models: critical elements, associations, connections, specific happenings, and antecedents.

Main Results:

• Demonstrated the combination of ESA with process-tracing tests for grounding counterfactual causal inferences.
• Showcased the integration of ESA with network analysis for exploring quantitative patterns in event structures.
• Exemplified analytical approaches using a case study on capability construction for open innovation management.

Conclusions:

• ESA, when enhanced with causal process tracing and network analysis, offers a powerful framework for process research.
• The proposed analytical methods provide novel ways to study complex event structures in management and engineering.
• This integrated approach strengthens causal inference and quantitative analysis in management and engineering studies.