THE EFFECT OF AI APPLICATIONS AND DIGITAL TRANSFORMATION ON CORPORATE INNOVATION PERFORMANCE IN GLOBAL AUTOMOTIVE ENTERPRISES

Abstract

This dissertation investigates the impact of AI-driven digital transformation on innovation performance within automotive enterprises. As the automotive industry faces significant shifts due to technological advancements, the study examines how various dimensions of digital transformation affect firms' innovation capabilities. Independent variables include Artificial Intelligence (AI) applications, Depth of Digital Transformation, and Breadth of Digital Transformation, which represent different facets of how digital tools and processes are integrated into operations. The dependent variable, Innovation Performance, measures how effectively these innovations translate into competitive advantages.

The research also explores Digital Capabilities as a mediating variable, positing that stronger digital skills and resources enhance the relationship between AI-driven transformation and innovation. Furthermore, Firm Size acts as a moderating variable, assessing how organizational scale influences the effects of digital transformation. Control variables, such as Industry Type and Market Competition, ensure that external factors do not distort the findings. Additionally, Regulatory Policies and Technological Progress are included as external variables, examining their broader impacts on both digital transformation and innovation performance.

This study aims to provide insights into how AI and digitalization reshape innovation in automotive enterprises, offering both theoretical contributions and practical implications for industry leaders.