Boost your research success in business studies and economics
The ZBW Open Economics Guide shows you how to use Open Science methods and tools – such as Open Access and Open Data – to make your research more efficient and visible!
Introduction to Open Access
Making research visible.
Introduction to Open Data
Making research verifiable.
Introduction to Open Code
Making research transparent.
Introduction to OER
Making teaching better.
This is how Open Science works in research practice!
Free Open Science Tools
A whole range of free and useful Open Science tools are available to support you in making your research even more efficient. Take a look at our tool catalogue!
New Blog Posts
Stay up to date with the latest tips and tutorials on Open Science.
Three in One for Open Science: Wharton Credibility Lab’s Toolbox Supports Researchers’ Workflow
Making Open Science irresistibly easy is the Wharton Credibility Lab’s mission....
Open Access Tool ShareYourPaper: Free Your own Journal Articles From Paywalls
You have published an article in a journal, but it is...
Open Science in Practice
Researchers' inside reports from their everyday life.
Open Science Events
Conferences, seminars, webinars, online panels and more!
KI und Metadaten
Mit Hilfe von künstlicher Intelligenz OER-Materialien verschlagworten.
Quantitative Empirical Accounting Research and Open Science Methods
This course focuses on quantitative empirical accounting research, covering theoretical, methodological and technical aspects of this research program. It also introduces students to the concepts of Open Science. In terms of applications, it concentrates on financial and other related disclosure issues but also touches on some managerial and auditing topics. After this course, participants should have a clear understanding about the theoretical foundations of quantitative empirical accounting research, know the methodological approaches to and common pitfalls of empirical research designs, have become familiar with a collaborative open science workflow using R/Python/Stata and Github, know how to execute empirical archival studies, including the usability and inter-operability of different data sources and, based on their own research proposal, have received constructive feedback on how to design and execute a viable study in the area of quantitative empirical accounting research.
First part, online: 01.09.24, 04.09.26, 08.09.26, 11.09.26
Second part, in person (Berlin): September 16 - 18, 2026
Contact
Do you have questions about Open Science or suggestions for our guide?
We look forward to hearing from you!
