My Research Interest ​
Evaluation of Critical Success Factors for Competitive Advantage in New Product Development of Medical Imaging Devices
​
Motivation
Medical imaging device (MID) development demands an intricate balance between engineering innovation, regulatory compliance, and market responsiveness. Despite technological advances, many companies struggle to translate R&D efforts into sustainable market advantage. My research investigates the underlying Critical Success Factors (CSFs) that determine whether new medical imaging products succeed or fail in global markets.
​
Research Approach
A quantitative research design was applied to identify and validate key CSFs influencing competitive advantage.
-
Sample: 333 survey responses from professionals across Europe, North America, and Asia
-
Independent variables: Organizational capability, market orientation, execution excellence, cost efficiency, and product strategy
-
Methodology: Statistical analysis and structural equation modeling were used to assess the strength and mediation of relationships among variables.
Key Findings
-
Product Strategy and Regulatory Effectiveness emerged as the strongest predictors of competitive advantage.
-
Other CSFs—such as market orientation, cost efficiency, and execution excellence—showed indirect effects, mediated through regulation and strategy.
-
The analysis led to the creation of a conceptual framework called the “Diamond of MID Success”, capturing the interdependencies among these factors.
Key Findings & Contributions
-
Product Strategy and Regulation emerged as the most significant levers influencing competitive advantage in MID development, both directly and via interaction effects.
-
Other variables (market orientation, cost efficiency, execution excellence) exerted influence more strongly when mediated through regulation and strategy, rather than direct paths.
-
I distilled these into a conceptual “Diamond of MID Success” model, highlighting interdependencies among these factors.
-
Based on empirical evidence, I propose actionable best practices for both academia and industry to structure R&D and strategic planning.
Broader future research topics- I am carrying out now
​
-
Integrate AI and ML to accelerate design decisions and innovation speed.
-
Strengthen supply chain resilience through digital visibility and predictive analytics.
-
Build data-connected ecosystems enabling real-time collaboration and faster execution.
-
Digital twin on enhancing quality and speed
-
Apply generative AI to optimize innovation workflows and investment prioritization.
-
Embed sustainability and ESG metrics within adaptive innovation management frameworks.
