Bureaucratic adaptation to policy change: a mixed-methods study of organizational learning, digital readiness, and local social capital

Abstract

Local bureaucracies must translate frequent policy changes into workable routines despite hierarchical procedures, uneven employee capacity, and unequal digital infrastructure. This study examines bureaucratic adaptation in the Boalemo Regency Government through a convergent descriptive mixed-methods design grounded in organizational adaptive capacity, organizational learning, digital readiness, and social capital. Survey data were obtained from 185 civil servants selected through proportional random sampling, and qualitative evidence was collected from 15 purposively selected officials and staff through interviews, participatory observation, and document review. Quantitative data were summarized using means, achievement percentages, and frequency distributions; qualitative data were analyzed through reduction, display, and conclusion verification. The two strands were integrated by comparing convergence and divergence across the same analytical dimensions. Organizational learning capacity had the highest mean (M = 3.94), followed by structural flexibility (M = 3.82) and policy responsiveness (M = 3.75). Openness to innovation (M = 3.88) exceeded the speed of digital migration (M = 3.42), indicating a descriptive gap between behavioral willingness and implementation readiness. Qualitative findings showed that pohala'a-based kinship supported informal coordination, while red tape, uneven village-level capacity, and infrastructure constraints limited implementation. The findings support an Adaptive Bureaucracy Cycle that links people development, process simplification, culture, and digital support. Because the design is cross-sectional and the reported statistics are descriptive, the results identify patterns and plausible mechanisms rather than causal effects.