Automated decision support systems in innovation : the role of decision support systems in marketing and product development

Abstract

Automated Decision Support Systems (DSS) have changed the management of innovation at its very core by allowing quicker, fact-based, and scalable decision-making. This thesis explains how DSS affects marketing and product development processes compared to traditional models of innovation, which rely heavily on expert intuition and sequential processes. Through case studies of Amazon's dynamic pricing technology and Tesla's AI-driven autonomous vehicle revolution, this research puts operational advantages like diminutive decision cycles, improved scalability, and improved customer responsiveness in the spotlight. Research evidence suggests that DSS-informed innovation models outperform traditional methods in dynamic market environments, though requiring careful integration of human decision-making, ethical safeguards, and cultural adaptability. The study offers strategic advice to firms contemplating DSS adoption, with an emphasis on hybrid human-AI collaboration and stepwise implementation techniques.