DATA-DRIVEN PUBLIC ADMINISTRATION: A CASE STUDY OF THE OFFICE OF THE NATIONAL LAND POLICY BOARD

Abstract

This research aimed to 1) study the level of data-driven public organization  of the Office of the National Land Policy Board according to the requirements of the Organization for Economic Co-operation and Development from the perspective of personnel; 2) study the different personal factors of personnel leading to different perspectives on data-driven public organization of the Office of the National Land Policy Board; and 3) study the guidelines for developing the Office of the National Land Policy Board into a data-driven public organization according to the international standards set by the Organization for Economic Co-operation and Development. Data were collected from 198 personnel of the Office of the National Land Policy Board via questionnaires and analyzed using descriptive statistics including percentage, frequency, mean, and standard deviation were used to describe the general characteristics of the data. For hypothesis testing, inferential statistics were applied using one-way analysis of variance (ANOVA). When a statistically significant difference was found, pairwise comparisons were conducted using the Least Significant Difference (LSD) method at the 0.05 level of statistical significance. The research results found that the overall level of data-driven public organization of the Office of the National Land Policy Board was at a high level, but had not yet achieved the criteria set in this research study. When classified by personal factors, it was found that gender, age, education level, job position, job position level, and length of employment had different perspectives on data-driven public organization. The guidelines for organizational development should focus on developing and enhancing personnel’s potential in systematic data management. Along with the development of technological infrastructure for efficient data linkage and fostering a culture of using data in decision-making and management to elevate to the standard of data-driven public sector at the international level.