Understanding the Causes of Open Innovation Failure: A Quantitative Study

11. April 2025

Open Innovation (OI) has become a cornerstone of modern innovation strategy, enabling firms to collaborate with external partners, users, and communities to accelerate innovation. While the benefits of OI are widely documented, many organizations face significant challenges that lead to partial or complete failure of OI initiatives. These failures can stem from a range of factors, including organizational culture, misaligned expectations, lack of trust, poor knowledge integration, or weak governance structures.

Despite the increasing adoption of OI practices, the systematic understanding of why OI initiatives fail remains underdeveloped in academic literature—particularly from a quantitative, empirical perspective. This master’s thesis will investigate the causes and patterns of failure in open innovation using a quantitative-based research design. The goal is to collect and analyze data from organizations that have engaged in OI initiatives, with a focus on identifying key failure factors and potential moderating influences such as industry type, firm size, or collaboration model.

Level Master
Language English
Field of Study Business Administration, Information Systems, Management, or related fields
Prerequisites
  • Interest in open innovation and innovation management
  • Basic knowledge of survey design and statistical analysis (e.g., correlation and regression analysis)
  • Familiarity with quantitative research methods (e.g., SmartPLS, SPSS, R, or Python for data analysis)

Description

This thesis aims to explore the underlying reasons for failure in Open Innovation (OI) initiatives through the lens of quantitative empirical research. The student will design and distribute a structured survey targeting professionals involved in OI projects across various industries.

Key research objectives include:

  • Identifying the most common causes of OI failure as reported by practitioners

  • Testing the relationship between organizational, strategic, and relational factors and the likelihood of OI failure

  • Analyzing potential differences across industries, firm sizes, or innovation types

  • Exploring how companies recover from or learn from failed OI attempts

The findings will offer data-driven insights into the risks and challenges of managing OI and help organizations better design resilient innovation strategies.

Why Choose This Topic?

  • Real-World Impact – Understand the practical reasons behind innovation breakdowns and help improve how organizations approach collaboration
  • Empirical Focus – Gain hands-on experience in survey-based research and quantitative analysis, valuable for both academic and industry careers
  • Novel Contribution – Address a relatively overlooked area in innovation research by providing fresh, data-backed insights into OI failure

How to Apply

If you are interested, please send the following via mail:

  • CV
  • Transcript of records
  • Short motivation

We look forward to hearing from you!

Contact Person

Joni Riihimäki (email: joni.riihimaeki@fau.de)