Analyzing Factors Influencing the Effectiveness of Technological Transformation in Logistics Enterprises: A Study Based on the VAR Model

With the rapid advancement of technologies such as artificial intelligence, blockchain, cloud computing, and big data, the logistics industry is facing significant opportunities for technological transformation. This paper utilizes a Panel Vector Autoregression (PVAR) model to investigate the factors influencing the effectiveness of technological transformation in logistics enterprises. Using data from 52 publicly listed logistics companies from 2013 to 2022, the study analyzes the impact of technological innovation capability, R&D intensity, development capability, risk management ability, and knowledge intensity on corporate performance. The results indicate a cointegration relationship between these factors and corporate performance, suggesting their long-term impact on the latter. Based on these findings, the paper recommends that logistics companies should lead with technological innovation, increase R&D investment, enhance development capabilities, and focus on cultivating technological talent and financial risk management. These recommendations aim to provide insights for the technological transformation of logistics enterprises.