Information resource management systems driven by intelligent algorithms are gradually changing the regional economic development model. Collaborative filtering algorithm optimizes resource allocation through user behavior records and provides accurate decision support for regional economic development. In this study, an information resource management system based on collaborative filtering algorithm is constructed, and its impact on regional economic development model is analyzed by multi-period double difference method. The study adopts MapReduce process to implement the collaborative filtering distributed screening recommendation algorithm, takes the average nighttime light brightness as the assessment index of regional economic development, selects 160 pilot prefecture-level cities as the experimental group and 150 prefecture-level cities as the control group, and analyzes the regional economic data from 2010 to 2020. The empirical results show that the information resource management system significantly improves the level of regional economic development, increasing the average nighttime light brightness in the pilot regions by about 2.29 and contributing 8.41% to economic growth. The system is effective in reducing the data error rate, and the promotion of the ratio of secondary and tertiary industries in the pilot cities in the eastern region is more obvious, with a coefficient of 0.0253 for the total population in employment. The number of end-of-year cell phone subscribers and telecom business revenue have a positive moderating effect on the high-quality development of the regional economy, with the coefficients of the triple difference term being 0.0092 and 0.0088, respectively. The study finds that information resource management has a significant impact on the economic efficiency, innovation drive, green ecology and sharing ability significantly, but the effect on coordination and optimization and cooperation and openness is not yet significant, indicating that the integration of intelligent algorithms and traditional industries still needs to be deepened.
