Factors and Indicators of Innovative Leadership of Private School Administrators in the Digital Era on the East Coast Southern Sub-Region of Thailand

Abstract

This article aims to study the factors and indicators of innovative leadership of private school administrators in the digital era and develop the structural model, factors, and indicators of innovative leadership of private school administrators in the digital era on the East Coast southern sub-region of Thailand and assess the congruence of the developed structural model with empirical data. The study was conducted by mixed methods and was divided into 2 phases. The first phase was to study the factors and indicators of innovative leadership of private school administrators by analyzing and synthesizing documents, concepts, theories, and research related to innovative leadership of school administrators that will lead organizations to compete in the digital era. The second phase was the research hypothesis assessment. Data was collected from a sample group of 580 school administrators and analyzed using statistics and AMOS software. The tools employed in data collection was a 5-level rating scale questionnaire with CVI, which was at 0.97, and the overall reliability value, determined from calculating Cronbach’s alpha coefficient, was at 0.98. The findings are as follows 1) The factors and indicators of innovative leadership of private school administrators in the digital era comprise 6 main factors, 23 sub-factors, and 116 indicators, which can be classified as 18 indicators of innovative vision, 13 indicators of Innovative creativity, 22 indicators of teamwork and innovation participation, 17 indicators of risk management, 22 indicators of creation of an innovative organizational atmosphere, and 24 indicators of personality and innovative role performance. 2) The developed structural model on innovative leadership indicators of school administrators shows congruence with empirical data, with chi-square = 209.017 with no statistical significance (p= .062), df = 179, Chi-square/df = 1.168 (less than 2). In addition, it was found that GFI = .970, AGFI = .954, CFI = .995, NFI = .966, RMSEA = .017, and RMR = .004.