In the face of a VUCA environment, organizational resilience has become a critical factor in sustaining enterprise performance. This study explores how digital transformation influences organizational resilience through its impact on the key components of organizational systems, specifically innovation capability and agile response. Using data from Chinese A-share listed firms over the period 2007–2023, the study finds that digital transformation significantly enhances organizational resilience, with robust results across various tests. The analysis highlights that digital transformation strengthens resilience by optimizing innovation capability and improving agility within organizational systems. Heterogeneity tests reveal that these effects are particularly strong in firms located in eastern and central regions, operating in capital-intensive industries, and at growth or maturity stages. These findings underscore the systemic role of digital transformation in building adaptive, resilient organizations that can better navigate uncertainty and complexity. This study contributes to understanding the dynamic interplay between digital technologies and organizational systems, offering practical insights for enterprises aiming to leverage digital transformation for sustainable growth and high-quality economic development.

The real estate market significantly influences individual lives, corporate decisions, and national economic sustainability. Therefore, constructing a data-driven, interpretable real estate market prediction model is essential. It can clarify each factor’s role in housing prices and transactions, offering a scientific basis for market regulation and enterprise investment decisions. This study comprehensively measures the evolution trends of the real estate markets in Beijing, Shanghai, Guangzhou, and Shenzhen, China, from 2003 to 2022 through three dimensions. Then, various machine learning methods and interpretability methods like SHAP values are used to explore the impact of supply, demand, policies, and expectations on the real estate market of China’s first-tier cities. The results reveal the following: (1) In terms of commercial housing sales area, adequate housing supply, robust medical services, and high population density boost the sales area, while demand for small units reflects buyers’ balance between affordability and education. (2) In terms of commercial housing average sales price, growth is driven by education investment, population density, and income, with loan interest rates serving as a stabilizing tool. (3) In terms of commercial housing sales amount, educational expenditure, general public budget expenditure, and real estate development investment amount drive revenue, while the five-year loan benchmark interest rate is the primary inhibitory factor. These findings highlight the divergent impacts of supply, demand, policy, and expectation factors across different market dimensions, offering critical insights for enterprise investment strategies.