Managing New Product Development processes in uncertain business environments

New Product Development (NPD) is critical to organizational growth and survival. In response to growing concerns over the limitations of traditional plan-driven processes, this Doctoral Thesis explores the integration and performance implications of flexible models in NPD through three complementary studies. The first study investigates the hybridization of plan-driven and flexible NPD models, identifying methodologies best suited for integration, effective integration stages, and contextual conditions favouring hybrid approaches. A systematic literature review and four case studies reveal that Agile, Design Thinking, and Lean Startup can be integrated into Stage-Gate models through nested or handed-over hybridization. Three hybrid types are outlined (Agile/Stage-Gate, Design Thinking/Stage-Gate, and Design Thinking and Lean Startup/Stage-Gate) along with four key decision-making dimensions (project type, market, technology, and learning gap) to guide R&D managers in model selection. The second study examines the relationship between NPD Agility and product innovation performance, considering the moderating role of project's innovation goals (incremental vs. radical). Using data from 88 NPD projects in the machinery and equipment industry, it identifies a positive but logarithmic relationship, indicating decreasing returns. This effect is significant for incremental innovation goals, but not for radical projects. The third study assesses the impact of Design Thinking, Lean Startup, and Agile learning cycles on new product performance under different levels of market ambiguity and market volatility. Based on 96 NPD projects in the machinery and equipment industry, it finds that Design Thinking and Agile positively affect performance, while Lean Startup does not. Design Thinking is more effective under high market ambiguity, Agile under low market ambiguity, while market volatility does not moderate these effects. Subgroup results further suggest Design Thinking is best suited to contexts where market ambiguity increases relative to, or together with, market volatility, while Agile seems better suited to environments with low market ambiguity and volatility.