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Smart city article details
| Title | Data-Driven Decision-Making Challenges Of Local Government In Indonesia |
|---|---|
| ID_Doc | 17408 |
| Authors | Sayogo D.S.; Yuli S.B.C.; Amalia F.A. |
| Year | 2024 |
| Published | Transforming Government: People, Process and Policy, 18, 1 |
| DOI | http://dx.doi.org/10.1108/TG-05-2023-0058 |
| Abstract | Purpose: This study aims to identify and outline the critical challenges affecting the inclination of executives to use data as the basis for making decisions at a local government level. Design/methodology/approach: The study conducted in-depth interviews with 21 public officials comprising middle- and top-level executives from 18 agencies and offices at the Bojonegoro Regency, one of Indonesia’s most progressive regencies in pursuing open government and smart cities. Findings: The findings demonstrate that ensuring a good quality data architecture, nurturing data culture and developing analytics capability are essential in the case of a developing country such as Indonesia. However, insufficient policies and regulations, a nonexistent evaluative framework for data quality, disruptive local tradition and the ingrained autocratic administration represent significant and unique challenges to implementing data-driven decision-making in the local government in Indonesia. Research limitations/implications: The chosen research approach may result in a need for more generalizability beyond Indonesia, accentuating the necessity for the geographical objects to include other developing countries in future research. Practical implications: The findings showcase that lack of awareness and acceptance from public officials and the general public of the importance of a data-driven approach; as such, a better understanding of the change in attitudes and mindsets of public officials is invariably one of the critical practical determinants. Originality/value: The findings signify the importance of creating robust accountability systems and evaluative frameworks that consider the many variables influencing decisions that capture the significance of organizational and local culture. © 2023, Emerald Publishing Limited. |
| Author Keywords | Data; Data-driven decision-making; Indonesia; Local government |
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