Abstract

The research objectives of this study were 1) to develop effectiveness indicators for the Branches of Guangxi Open University 2) to test the consistency of the structural relationship model of effectiveness indicators for the Branches of Guangxi Open University and 3) to develop administrative strategies to enhance the effectiveness of the Branches of Guangxi Open University. This research used a mixed method of qualitative and quantitative research. The research was conducted in three phases: Phase 1 involved identifying the key factors of administrative effectiveness through a literature review. Key indicators were refined through a focus group discussion with best practice university, Guizhou Open University. Phase 2 tested the consistency between the structural relationship model and empirical data. The sample consisted of 234 administrators and lecturers from 13 branches of Guangxi Open University. This research used muti-stage sampling, and the reliability of the questionnaire, which is one of the research instruments, is 0.980. The data were analyzed using correlation analysis and confirmatory factor analysis (CFA). Phase 3 developed strategies to enhance the administrative effectiveness of the branches, based on the results of Phase 2. The sample group consists of 3 stakeholders from Guangxi Open University by using purposive sampling, and the interview instrument is semi-structured Interview. Besides, the evaluation of the appropriateness of the strategy was evaluated by experts.

The findings could be summarized as follows: 1) Seven factors identified as influencing the administrative effectiveness of the branches: Human Resource Management, Regulatory Compliance and Governance System, Organizational Structure, Financial Management, Strategic Planning, Administrative Leadership, and Technological Integration in University Administration. These encompassed 27 specific indicators. 2) The structural relationship model for effectiveness indicators demonstrated a high level of consistency with empirical data. Fit indices included a Chi-square value of 175.16, degrees of freedom (df) of 148, a P-value of 0.063, and an RMSEA value of 0.028. 3) The proposed 18 strategies were highly rated for accuracy, propriety, and utility, with feasibility rated as high.

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