Research on the impact of Changan Automobile's digital transformation on financial performance
Year: 2025
Type: article
Abstract: Against the backdrop of rapid advancements in modern information technology, digital transformation has emerged as a global trend. This process has experienced unprecedented acceleration, particularly under the impact of the COVID-19 pandemic. Such transformation extends beyond technological innovation, encompassing critical aspects of corporate future competitiveness as well as organizational survival and growth within intensely competitive markets. As the global economy gradually recovers from the pandemic, sustaining digital transformation poses a significant challenge for enterprises. Governments worldwide have clearly recognized this imperative and have formulated corresponding strategic plans. Since 2015, China has implemented the "National Big Data Strategy," aiming to leverage big data to drive comprehensive economic growth and empower various industries. The "14th Five-Year Plan and Long-Range Objectives Through 2035," proposed in 2020, further emphasized the importance of accelerating the integration of the digital economy with traditional industries and building internationally competitive digital industrial clusters. Notably, the 2022 Government Work Report mentioned the "digital economy" for the sixth consecutive year, and for the first time, dedicated an entire paragraph to this topic, underscoring the government's heightened focus on its significance. Evidently, with continuous policy support and active participation from all sectors of society, digital transformation is poised to become a crucial driver for enterprises to navigate the future. This study selects Changan Automobile as a case study to analyze the motivations, pathways, and financial performance impacts of digital transformation in the automotive industry. The findings aim to provide insights and references for other enterprises within the sector.
Authors: Yuxuan Cheng, Zihan Dai
Institution: Shandong Institute of Business and Technology
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4409273835