Coast Guard’s performance: Impacts of interorganizational relations and IT adoptions
Bibliographic record
Abstract
This study examines how interorganizational relations and IT adoption influence strategic alliance performance and institutional effectiveness within the Indonesian Coast Guard (Bakamla), the central coordinating body in Indonesia’s fragmented maritime security system. It emphasizes structural and relational mechanisms- namely coordination, cooperation, and technological infrastructure- as key drivers of organizational performance. Data collected from 136 personnel engaged in multi-agency maritime operations were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that both interorganizational relations and IT adoption significantly improve strategic alliance performance which, in turn, fully mediates their effect on organizational performance. These findings highlight the importance of institutional trust and digital integration in enhancing cross-agency coordination and strengthening maritime governance in archipelagic contexts. ------------------------------------------------------------------------------Cite this article: APA Style:Prasetia, A., Kuncoro, E. A., Kartono, R., & Soepriyanto, G. (2026). Coast Guard’s performance: Impacts of interorganizational relations and IT adoptions. Maritime Technology and Research, 8(2), 281541. https://doi.org/10.33175/mtr.2026.281541 MDPI Style:Prasetia, A.; Kuncoro, E. A.; Kartono, R.; Soepriyanto, G. Coast Guard’s performance: Impacts of interorganizational relations and IT adoptions. Marit. Technol. Res. 2026, 8, 281541. https://doi.org/10.33175/mtr.2026.281541 Vancouver Style:Prasetia A, Kuncoro EA, Kartono R, Soepriyanto G. (2026). Coast Guard’s performance: Impacts of interorganizational relations and IT adoptions. Marit. Technol. Res. 2026, 8(2):281541. https://doi.org/10.33175/mtr.2026.281541 ------------------------------------------------------------------------------ Highlights Interorganizational relations and IT adoption improve alliance performance Strategic alliances mediate organizational effectiveness Weak authority limits direct performance impact Digital integration needs shared governance and trust Strengthening alliance governance enhances maritime coordination
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".