## 1 Introduction  
In the face of rapid urbanization, there is an increasing demand for transportation, resulting in increasingly serious traffic congestion and exhaust pollution. Many cities in China are rapidly advancing the construction of rail transit [1, 2]. As of February 2022, the subway lines that have been opened in the built-up area of Xi'an include Line 1, Line 2, Line 3, Line 4, Line 5, Line 6, Line 9, and Line 14. The total running mileage is 252.6 km. The urban public transport share of rail transit has surpassed 50%. However, with the rapid construction of urban rail transit, many problems regarding station area land use have been exposed. These include poor overall spatial efficiency, the underutilization of station area facilities and resources due to low passenger flow at certain stations, and congestion during peak periods caused by the dominance of single land use types at some stations. Station area spatial efficiency still has room for optimization in terms of land use, traffic profile, social efficiency, and spatial quality [3, 4, 5, 6, 7]. However, blindly optimizing station area land use cannot effectively solve the problems with station area land use. By scientifically and effectively measuring the spatial efficiency of station areas, the characteristics of station areas with different efficiencies are summarized. Through short-term optimization, the land use of inefficient station areas can be effectively developed and utilized [8; 9], and the land use of overloaded station areas can be reasonably controlled. Guided by principles of high-efficiency development for station areas, this paper investigates the \"efficiency\" of rail transit station areas from multiple perspectives. It develops an evaluation system for assessing station area spatial efficiency, with the goals of identifying effective solutions to address inefficiencies in rail transit station areas and providing some guidance for the high-efficiency use of rail transit facilities [10; 11; 12]. The models used for spatial efficiency evaluation include the \"pressure-state-response\" model [13], the AHM-entropy weight composite method, data envelopment analysis (DEA) [14], the fuzzy evaluation method, and Digital Twin technology [15]. Among these, Digital Twin technology and the DEA model are particularly prominent in the field of rail transit. [PERSON] et al. [15] integrated Digital Twin technology with Building Information Modeling (BIM), significantly enhancing the maintenance efficiency and sustainability of railway systems. However, their focus was primarily on the dynamic management and resource optimization of railway infrastructure, lacking systematic quantitative analysis of the input-output relationship when evaluating spatial efficiency in station areas. In contrast, the DEA method, as a well-established efficiency evaluation tool [16; 17], is capable of comprehensively analyzing spatial efficiency in station areas under multi-input and multi-output scenarios, making it an ideal choice for assessing station efficiency. With the continuous development and widespread application of the DEA method, it has become a core tool for efficiency evaluation across various industries [18; 19; 20; 21]. However, this research approach has been underutilized for evaluating the efficiency of rail transit station areas. At present, most of the existing research on rail transit evaluation focuses on the theoretical analysis of station area spatial efficiency, the establishment of an evaluation index system, and the countermeasures to improve station area spatial efficiency [22; 23; 24; 25]. There are few studies evaluating station area spatial efficiency from the input-output perspective. Research on station area spatial efficiency based on the DEA method is lacking. According to the development stage of the DEA method [26; 27; 28; 29], the efficiency evaluation includes CCR, BCC, and SBM, which are widely used in various fields.