Abstract: Exploring how advancements in data analysis technologies influence investors' information acquisition motivations and capital market efficiency is an inherent requirement for the implementation of the "Five Major Articles" in finance and a key pathway to promoting high-quality financial development. This paper categorizes the progress of data analysis technologies into two types based on their driving forces: one is the micro-level "input-driven" technological progress, where investors increase research and development investments, and the results of such investments are uncertain; the other is the macro-level "environment-driven" technological progress, which involves improving data infrastructure and enhancing data-sharing mechanisms. Using a rational expectations model, this paper compares the impacts of these two types of technological progress on information acquisition and capital market efficiency. The findings are as follows: (1) Under the dual effects of rising opportunity costs and intensified free-rider effects, "input-driven" technological progress suppresses information acquisition and weakens market efficiency. (2) Although "environment-driven" technological progress is also impacted by free-rider effects, it can still enhance information acquisition and improve market efficiency by improving the accuracy of asset return predictions. (3) After incorporating the substitution relationship between traditional technologies and data analysis technologies in information acquisition into the model, the direction of the impact on capital market efficiency remains unchanged for both types of technological progress. However, factors such as risk aversion, free-riding, and opportunity costs reduce investors' willingness to adopt data analysis technologies, thereby diminishing the impact of both types of technological progress on capital market efficiency. To fully realize the dividends of data analysis technology, it is not sufficient to rely solely on micro-level input-driven progress; comprehensive support is also needed at the macro level through the improvement of data systems and data infrastructure, which is essential for building a high-quality modern capital market with Chinese characteristics.

Key words: data analytics technologies, input-driven, environment-driven, information acquisition, capital market efficiency