The Impact of Digital Transformation on Enterprise Operations: Mechanisms, Practices, and Challenges—An Empirical Study Based on the Technology Acceptance Model and Multiple Case Studies

Abstract

Against the backdrop of the accelerating penetration of the global digital economy and the restructuring of global value chains, digital transformation has become a core strategy for enterprises to reconstruct their competitive advantages. However, in practice, the contradiction of “high investment and low return” is prevalent, necessitating a systematic understanding of the mechanisms and implementation paths of dig-ital transformation. This study integrates the Technology Acceptance Model (TAM) and Resource-Based Value (RBV) to construct a three-dimensional analytical framework of “technology penetra-tion-organizational adaptation-ecosystem synergy.” Based on panel data of A-share listed companies in Shanghai and Shenzhen (2018–2023), this study empirically examines the impact mechanisms of digital transformation on corporate operational risk, innovation performance, and supply chain resilience using fixed-effects models, spatial Durbin models, and machine learning methods. The study finds that: (1) Digital transformation significantly reduces operational risk by improving information transparency and internal control quality, with information transparency and internal control quality accounting for 32.7% and 24.5% of the mediating effects, respectively; (2) Organizational agility positively moderates the impact of digital transformation on innovation performance, while environmental uncertainty strengthens its empowering effect on supply chain resilience; (3) Digital transformation exhibits a “critical majority” effect, with the risk reduction effect being significantly released only when the technology penetration rate exceeds 0.42. The study also proposes a phased implementation path (initiation phase → diffusion phase → deepening phase → reconstruction phase), industry-differentiated solutions (manufacturing: “equipment cloud + AI quality inspection”, retail: “O2O + private domain traffic”, finance: “open banking + robo-advisors”), and lightweight transformation strategies for SMEs (SaaS tool replacement, focusing on core scenarios). Finally, addressing risks such as technology lock-in and data monopoly, it constructs a response system of “dynamic risk management—policy tool synergy,” and provides practical suggestions through international comparisons and failure case studies. This study provides policymakers with theo-retical basis and operational guidelines for optimizing digital transformation support policies and for enterprises to avoid transformation pitfalls.