Survey Division

Survey Research Operation and Development (SROD) was established in 1993 by the Center of Survey Research (CSR), and is devoted to the collection of high-quality survey data and the development of state-of-the-art survey technology. SROD mainly assists academic clients in conducting face-to-face, telephone, web, and mixed-mode surveys. We also conduct cognitive interviews, and focus groups discussions. Face-to-face surveys include probability sample surveys and panel surveys. Telephone surveys include landline and mobile phone surveys, while web surveys include e-mail and opt-in web surveys. SROD aims to continuously improve the quality of survey data, to develop standardized field-work procedures, to systematically analyze paradata, and to invest in the development of survey technology.

From project proposal, and survey implementation, to project report, SROD provides customized, high quality, and advanced services as follows.
• Consultation: survey, sample and questionnaire designs and survey implementation
• Budget planning
• Sample design
• Sample weighting
• Questionnaire design
• Interviewer recruitment, training and management
• Project management
• Data collection and management
• Data processing and analysis
• Project report

• CAI System: CSR has developed a multi-mode, computer-assisted interviewing system (multi-mode CAI system) since 2012, which    integrates CAPI, CATI, CAWI, and CAI DataSis systems, reduces the cost and errors of surveys, and improves the efficiency of the execution    process and the quality of data. CAPI system is compatible with both Windows and Android (Tablet App) devices. We also lease the CAI    software system to researchers and organizations outside CSR.
• CATI Lab: SROD operates a CATI Lab with 49 interviewer stations and 5 supervisor stations.
• Focus Group Room: SROD is equipped with a focus group room.

Research and Development
SROD specializes in cutting-edge survey technology and seeks to actively advance research on survey methods including:
• Improving the efficiency of data collection
• Reducing total survey error
• Using paradata to assess survey errors
• Inventing new measurements